Search results for: logs

Authors: Mohd Zaki Hamzah, Roslan Rani, Ahmad Bazli Razali, Satiful Bahri Mamat, Abdul Hadi Ripin, Mohd Harun Esa

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Ever since 1901, forest management and silviculture practices in Malaysia have been frequently reviewed and updated to take into account changes in forest conditions, markets, timber demand/supply and technical advances that can be achieved in industrial processes, logging and forest harvesting, and currently, the forest management system practiced in Peninsular Malaysia is the Selective Management System (SMS) which was introduced in 1978. This system requires the selection of management regime (felling) based on Pre-Felling Forest Inventory (Pre-F) data to ensure economical harvesting and also ensuring adequate standing stands for subsequent rounds of felling, while maintaining ecological balance and environmental quality. SMS regulates forest harvesting through area and volume controls, with the cutting cycle 30 years. Most of the forest management units (FMU) (in Peninsular Malaysia) implementing SMS have been certified by Forest Stewardship Council (FSC) and/or Program for Endorsement of Forest Certification (PEFC), and one such FMU belongs to Kumpulan Pengurusan Kayu Kayan Terengganu (KPKKT). KPKKT, a timber management subsidiary of Golden Pharos Berhad (GPB), adopts the SMS to manage its 108,900 ha of timber concessionary areas in its role as logs’ supplier for the consumption of three subsidiaries of GPB. KPKKT is also responsible for the sustainable development and management of its concession in accordance with the Sustainable Forest Management (SFM) standards to ensure that it addresses the loss of forest cover and forest degradation, forest-based economic, social and environmental benefits, and ecologically protecting forests while mobilising financial resources for the implementation of sustainable forest management planning, harvesting, monitoring and the marketing of products. This paper will detail out the management and harvesting guidelines imposed by the controlling government agency, and harvesting processes taken by KPKKT to comply with guidelines and eventually supplying timber to the relevant subsidiaries (downstream mills under GPB).

Keywords: sustainable forest management, silviculture, reduce impact logging, forest certification

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

Procedia PDF Downloads 228

Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 157

Authors: Yuvarani Naidu, Yasmeen Siddiqui, Mohd Yusof Rafii , Abu Seman Idris

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Sustainability of oil palm production in Southeast Asia, especially in Indonesia and Malaysia, is jeopardized by Ganoderma boninense, the fungus which causes basal stem rot (BSR) in oil palm. The root contact with unattended infected debris left in the plantations during replanting is known to be the primary source of inoculum. Abiding by the law, potentially effective technique of managing Ganoderma infected oil palm debris is deemed necessary because of the zero-burning policy in Malaysian oil palm plantations. White-rot hymenomycetes antagonistic to Ganoderma sp were selected to test their efficacy as log treatments in degrading Ganoderma infected oil palm logs and to minimize the survival of Ganoderma inoculum. Decay rate in terms of mass loss was significantly higher after the application of solid-state cultivation (SSC) of Trametes lactinea FBW (64% ±1.2), followed by Pycnoporus sanguineus FBR (55% ±1.7) in infected log block tissues, after 10 months of treatments. The degradation pattern was clearly distinguished between the treated and non-treated log blocks with the developed SSC formulations. The control infected log blocks showed the highest, whereas infected log blocks treated with either P. sanguineus FBR or T. lactinea FBW SSC formulations exhibited statistically lowest number of Ganoderma spp. recovery on Ganoderma Selective Medium (GSM), after 8 months of treatment. Out of that, the lowest recovery of Ganoderma spp. was reported in infected log blocks inoculated with the strain T. lactinea FBW (21% ± 0.9) followed by P. sanguineus FBR (33% ± 2.2), after 8 months, Further, no recovery of Ganoderma was noticeable, 10 months after treatment applications in log blocks treated with both of the formulations. This is the first nursery-base study to substantiate the initial colonization of white-rot hymenomycetes on oil palm log blocks previously infected with BSR pathogen, G. boninense. The present study has indicated that log blocks treatment with white-rot hymenomycetes significantly affected the mass loss of diseased and healthy log block tissues. This study provides a basis of biotechnological approaches inefficient degradation of oil palm-generated crop debris, under natural conditions with an ultimate aim of reducing the Ganoderma inoculum under heavy BSR infection pressure in eco-friendly manner.

Keywords: basal stem rot disease, ganoderma boninense, oil palm, white-rot fungi

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Authors: Dorota Zielińska, Monika Trząskowska, Anna Łepecka, Katarzyna Neffe-Skocińska, Beata Bilska, Marzena Tomaszewska, Danuta Kołożyn-Krajewska

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Minimum durability date (MDD) labeled food is known to have a long shelf life. A properly stored or transported food retains its physical, chemical, microbiological, and sensory properties up to MDD. The aim of the study was to assess the sensory quality and microbiological safety of selected thermally processed products,i.e., mayonnaise, jam, and canned tuna within and after MDD. The scope of the study was to determine the markers of microbiological quality, i.e., the total viable count (TVC), the Enterobacteriaceae count and the total yeast and mold (TYMC) count on the last day of MDD and after 1 and 3 months of storage, after the MDD expired. In addition, the presence of Salmonella and Listeria monocytogenes was examined on the last day of MDD. The sensory quality of products was assessed by quantitative descriptive analysis (QDA), the intensity of differentiators (quality features), and overall quality were defined and determined. It was found that during three months storage of tested food products, after the MDD expired, the microbiological quality slightly decreased, however, regardless of the tested sample, TVC was at the level of <3 log cfu/g, similarly, the Enterobacretiaceae, what indicates the good microbiological quality of the tested foods. The TYMC increased during storage but did not exceed 2 logs cfu/g of product. Salmonella and Listeria monocytogenes were not found in any of the tested food samples. The sensory quality of mayonnaise negatively changed during storage. After three months from the expiry of MDD, a decrease in the "fat" and "egg" taste and aroma intensity, as well as the "density" were found. The "sour" taste intensity of blueberry jam after three months of storage was slightly higher, compared to the jam tested on the last day of MDD, without affecting the overall quality. In the case of tuna samples, an increase in the "fishy" taste and aroma intensity was observed during storage, and the overall quality did not change. Tested thermally processed products (mayonnaise, jam, and canned tuna) were characterized by good microbiological and sensory quality on the last day of MDD, as well as after three months of storage under conditions recommended by the producer. These findings indicate the possibility of reducing food losses by extending or completely abolishing the MDD of selected thermal processed food products.

Keywords: food wastes, food quality and safety, mayonnaise, jam, tuna

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Authors: Nasser Al-Azmi, Al-Sabea Salem, Abu-Eida Abdullah, Milan Patra, Mohamed Elyas, Daniel Freile, Larisa Tagarieva

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Well intervention was done along with Production Logging Tools (PLT) to detect sources of water, and to check well integrity for two West Kuwait oil wells started to produce 100 % water. For the first well, to detect the source of water, PLT was performed to check the perforations, no production observed from the bottom two perforation intervals, and an intake of water was observed from the top most perforation. Then a decision was taken to extend the PLT survey from tag depth to the Y-tool. For the second well, the aim was to detect the source of water and if there was a leak in the 7’’liner in front of the upper zones. Data could not be recorded in flowing conditions due to the casing deformation at almost 8300 ft. For the first well from the interpretation of PLT and well integrity data, there was a hole in the 9 5/8'' casing from 8468 ft to 8494 ft producing almost the majority of water, which is 2478 bbl/d. The upper perforation from 10812 ft to 10854 ft was taking 534 stb/d. For the second well, there was a hole in the 7’’liner from 8303 ft MD to 8324 ft MD producing 8334.0 stb/d of water with an intake zone from10322.9-10380.8 ft MD taking the whole fluid. To restore the oil production, W/O rig was mobilized to prevent dump flooding, and during the W/O, the leaking interval was confirmed for both wells. The leakage was cement squeezed and tested at 900-psi positive pressure and 500-psi drawdown pressure. The cement squeeze job was successful. After W/O, the wells kept producing for cleaning, and eventually, the WC reduced to 0%. Regular PLT and well integrity logs are required to study well performance, and well integrity issues, proper cement behind casing is essential to well longevity and well integrity, and the presence of the Y-tool is essential as monitoring of well parameters and ESP to facilitate well intervention tasks. Cost and time optimization in oil and gas and especially during rig operations is crucial. PLT data quality and the accuracy of the interpretations contributed a lot to identify the leakage interval accurately and, in turn, saved a lot of time and reduced the repair cost with almost 35 to 45 %. The added value here was more related to the cost reduction and effective and quick proper decision making based on the economic environment.

Keywords: leak, water shut-off, cement, water leak

Procedia PDF Downloads 117

Authors: Mariia Khramova, Sergio Martinez, Duc Nguyen

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Modern electronic devices, particularly smartphones, are characterised by extremely high environmental footprint and short product lifecycle. Every year manufacturers release new models with even more superior performance, which pushes the customers towards new purchases. As a result, millions of devices are being accumulated in the urban mine. To tackle these challenges the concept of circular economy has been introduced to promote repair, reuse and recycle of electronics. In this case, electronic devices, that previously ended up in landfills or households, are getting the second life, therefore, reducing the demand for new raw materials. Smartphone reuse is gradually gaining wider adoption partly due to the price increase of flagship models, consequently, boosting circular economy implementation. However, along with reuse of communication device, circular economy approach needs to ensure the data of the previous user have not been 'reused' together with a device. This is especially important since modern smartphones are comparable with computers in terms of performance and amount of data stored. These data vary from pictures, videos, call logs to social security numbers, passport and credit card details, from personal information to corporate confidential data. To assess how well the data privacy requirements are followed on smartphones second-hand market, a sample of 100 Android smartphones has been purchased from IT Asset Disposition (ITAD) facilities responsible for data erasure and resell. Although devices should not have stored any user data by the time they leave ITAD, it has been possible to retrieve the data from 19% of the sample. Applied techniques varied from manual device inspection to sophisticated equipment and tools. These findings indicate significant barrier in implementation of circular economy and a limitation of smartphone reuse. Therefore, in order to motivate the users to donate or sell their old devices and make electronic use more sustainable, data privacy on second-hand smartphone market should be significantly improved. Presented research has been carried out in the framework of sustainablySMART project, which is part of Horizon 2020 EU Framework Programme for Research and Innovation.

Keywords: android, circular economy, data privacy, second-hand phones

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Authors: Tawfig Alghbaili

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LP3D Field is located near the center of the Sirt Basin in the Marada Trough approximately 215 km south Marsa Al Braga City. The Marada Trough is bounded on the west by a major fault, which forms the edge of the Beda Platform, while on the east, a bounding fault marks the edge of the Zelten Platform. The main reservoir in the LP3D Field is Upper Paleocene Beda Formation. The Beda Formation is mainly limestone interbedded with shale. The reservoir average thickness is 117.5 feet. To develop a better understanding of the characterization and distribution of the Beda reservoir, quantitative seismic data interpretation has been done, and also, well logs data were analyzed. Six reflectors corresponding to the tops of the Beda, Hagfa Shale, Gir, Kheir Shale, Khalifa Shale, and Zelten Formations were picked and mapped. Special work was done on fault interpretation part because of the complexities of the faults at the structure area. Different attribute analyses were done to build up more understanding of structures lateral extension and to view a clear image of the fault blocks. Time to depth conversion was computed using velocity modeling generated from check shot and sonic data. The simplified stratigraphic cross-section was drawn through the wells A1, A2, A3, and A4-LP3D. The distribution and the thickness variations of the Beda reservoir along the study area had been demonstrating. Petrophysical analysis of wireline logging also was done and Cross plots of some petrophysical parameters are generated to evaluate the lithology of reservoir interval. Structure and Stratigraphic Framework was designed and run to generate different model like faults, facies, and petrophysical models and calculate the reservoir volumetric. This study concluded that the depth structure map of the Beda formation shows the main structure in the area of study, which is north to south faulted anticline. Based on the Beda reservoir models, volumetric for the base case has been calculated and it has STOIIP of 41MMSTB and Recoverable oil of 10MMSTB. Seismic attributes confirm the structure trend and build a better understanding of the fault system in the area.

Keywords: LP3D Field, Beda Formation, reservoir models, Seismic attributes

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

Procedia PDF Downloads 187

Authors: Rahimah Saimin

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Previous research has shown that young children can learn from educational television programmes, videos or other technological media. However, the blending of any of these with traditional printed-based text appears to be omitted. Repeated viewing is an important factor in children's ability to comprehend the content or plot. The present study combined videos with traditional printed-based text and required repeated viewing and is original and distinctive. The first study was a pilot study to explore whether the intervention is implementable in ordinary classrooms. The second study explored whether the curricular embedding is important or whether the video with curricular embedding is effective. The third study explored the effect of “dosage”, i.e. whether a longer/ more intense intervention has a proportionately greater effect on outcomes. Both measured outcomes (comprehension, word sounds, and early word recognition) and unmeasured outcomes (engagement to reading traditional printed-based texts or/and multimodal texts) were obtained from this study. Observation indicated degree of engagement in reading. The theoretical framework was multimodality theory combined with Piaget’s and Vygotsky’s learning theories. An experimental design was used with 4-5-year-old children in nursery schools and primary schools. Six links to video clips exploring non-fiction science content were provided to teachers. The first session is whole-class and subsequent sessions small-group. The teacher then engaged the children in dialogue using supplementary materials. About half of each class was selected randomly for pre-post assessments. Two assessments were used the British Picture Vocabulary Scale (BPVSIII) and the York Assessment of Reading for Comprehension (YARC): Early Reading. Different programme fidelity means were deployed- observations, teacher self-reports attendance logs and post-delivery interviews. Data collection is in progress and results will be available shortly. If this multiphase study show effectiveness in one or other application, then teachers will have other tools which they can use to enhance vocabulary, letter knowledge and word reading. This would be a valuable addition to their repertoire.

Keywords: language skills, literacy skills, multimodality, video

Procedia PDF Downloads 339

Authors: Vinda B. Manurung, Laila Warkhaida, David Hutabarat, Sentanu Wisnuwardhana, Christovik Simatupang, Dhani Sanjaya, Ashadi, Redha B. Putra, Kiki Yustendi

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The geothermal drilling environment presents many obstacles that have limited the use of directional drilling and logging-while-drilling (LWD) technologies, such as borehole washout, mud losses, severe vibration, and high temperature. The case study presented in this paper demonstrates a practice to enhance data logging in geothermal drilling by deploying advanced telemetry and LWD technologies. This operation is aiming continuous improvement in geothermal drilling operations. The case study covers a 12.25-in. hole section of well XX-05 in Pad XX of the Sorik Marapi Geothermal Field. LWD string consists of electromagnetic (EM) telemetry, pressure while drilling (PWD), vibration (DDSr), and acoustic calliper (ACAL). Through this tool configuration, the operator acquired drilling mechanics and caliper logs in real-time and recorded mode, enabling effective monitoring of wellbore stability. Throughout the real-time acquisition, EM-PPM telemetry had provided a three times faster data rate to the surface unit. With the integration of Caliper data and Drilling mechanics data (vibration and ECD -equivalent circulating density), the borehole conditions were more visible to the directional driller, allowing for better control of drilling parameters to minimize vibration and achieve optimum hole cleaning in washed-out or tight formation sequences. After reaching well TD, the recorded data from the caliper sensor indicated an average of 8.6% washout for the entire 12.25-in. interval. Washout intervals were compared with loss occurrence, showing potential for the caliper to be used as an indirect indicator of fractured intervals and validating fault trend prognosis. This LWD case study has given added value in geothermal borehole characterization for both drilling operation and subsurface. Identified challenges while running LWD in this geothermal environment need to be addressed for future improvements, such as the effect of tool eccentricity and the impact of vibration. A perusal of both real-time and recorded drilling mechanics and caliper data has opened various possibilities for maximizing sensor usage in future wells.

Keywords: geothermal drilling, geothermal formation, geothermal technologies, logging-while-drilling, vibration, caliper, case study

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Authors: Patricia Jiménez, Rafael Corchuelo, Hassan A. Sleiman

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Web mining is gaining importance at an increasing pace. Currently, there are many complementary research topics under this umbrella. Their common theme is that they all focus on applying knowledge discovery techniques to data that is gathered from the Web. Sometimes, these data are relatively easy to gather, chiefly when it comes from server logs. Unfortunately, there are cases in which the data to be mined is the data that is displayed on a web document. In such cases, it is necessary to apply a pre-processing step to first extract the information of interest from the web documents. Such pre-processing steps are performed using so-called information extractors, which are software components that are typically configured by means of rules that are tailored to extracting the information of interest from a web page and structuring it according to a pre-defined schema. Paramount to getting good mining results is that the technique used to extract the source information is exact, which requires to evaluate and compare the different proposals in the literature from an empirical point of view. According to Google Scholar, about 4 200 papers on information extraction have been published during the last decade. Unfortunately, they were not evaluated within a homogeneous framework, which leads to difficulties to compare them empirically. In this paper, we report on an original information extraction evaluation method. Our contribution is three-fold: a) this is the first attempt to provide an evaluation method for proposals that work on semi-structured documents; the little existing work on this topic focuses on proposals that work on free text, which has little to do with extracting information from semi-structured documents. b) It provides a method that relies on statistically sound tests to support the conclusions drawn; the previous work does not provide clear guidelines or recommend statistically sound tests, but rather a survey that collects many features to take into account as well as related work; c) We provide a novel method to compute the performance measures regarding unsupervised proposals; otherwise they would require the intervention of a user to compute them by using the annotations on the evaluation sets and the information extracted. Our contributions will definitely help researchers in this area make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it will also help practitioners make informed decisions on which proposal is the most adequate for a particular problem. This conference is a good forum to discuss on our ideas so that we can spread them to help improve the evaluation of information extraction proposals and gather valuable feedback from other researchers.

Keywords: web information extractors, information extraction evaluation method, Google scholar, web

Procedia PDF Downloads 248

Authors: Jean Paul Muambangu Milambo, Peter Nyasulu, John Akudugu, Leonidas Ndayisaba, Joyce Tsoka-Gwegweni, Lebwaze Massamba Bienvenu, Mitshindo Mwambangu Chiro

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In 2018, non-communicable diseases (NCDs) were responsible for 48% of deaths in the Democratic Republic of Congo (DRC), with cancer contributing to 5% of these deaths. There is a notable absence of cancer registries, capacity-building activities, budgets, and treatment roadmaps in the DRC. Current cancer estimates are primarily based on mathematical modeling with limited data from neighboring countries. This study aimed to assess cancer subtype prevalence in Kinshasa hospitals and compare these findings with WHO model estimates. Methods: A retrospective observational study was conducted from 2018 to 2020 at HJ Hospitals in Kinshasa. Data were collected using American Cancer Society (ACS) questionnaires and physician logs. Descriptive analysis was performed using STATA version 16 to estimate cancer burden and provide evidence-based recommendations. Results: The results from the chart review at HJ Hospitals in Kinshasa (2018-2020) indicate that out of 6,852 samples, approximately 11.16% were diagnosed with cancer. The distribution of cancer subtypes in this cohort was as follows: breast cancer (33.6%), prostate cancer (21.8%), colorectal cancer (9.6%), lymphoma (4.6%), and cervical cancer (4.4%). These figures are based on histopathological confirmation at the facility and may not fully represent the broader population due to potential selection biases related to geographic and financial accessibility to the hospital. In contrast, the World Health Organization (WHO) model estimates for cancer prevalence in the DRC show different proportions. According to WHO data, the distribution of cancer types is as follows: cervical cancer (15.9%), prostate cancer (15.3%), breast cancer (14.9%), liver cancer (6.8%), colorectal cancer (5.9%), and other cancers (41.2%) (WHO, 2020). Conclusion: The data indicate a rising cancer prevalence in DRC but highlight significant gaps in clinical, biomedical, and genetic cancer data. The establishment of a population-based cancer registry (PBCR) and a defined cancer management pathway is crucial. The current estimates are limited due to data scarcity and inconsistencies in clinical practices. There is an urgent need for multidisciplinary cancer management, integration of palliative care, and improvement in care quality based on evidence-based measures.

Keywords: cancer, risk factors, DRC, gene-environment interactions, survivors

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Authors: Gabriel Efomeh Omolaiye, Jimoh Ajadi, Olatunji Seminu, Yusuf Ayoola Jimoh, Ubulom Daniel

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Identification and characterization of petrophysical properties of reservoirs in the Bima Formation were undertaken to understand their spatial distribution and impacts on hydrocarbon saturation in the highly heterolithic siliciclastic sequence. The study was carried out using nine well logs from Maiduguri and Baga/Lake sub-basins within the Borno Basin. The different log curves were combined to decipher the lithological heterogeneity of the serrated sand facies and to aid the geologic correlation of sand bodies within the sub-basins. Evaluation of the formation reveals largely undifferentiated to highly serrated and lenticular sand bodies from which twelve reservoirs named Bima Sand-1 to Bima Sand-12 were identified. The reservoir sand bodies are bifurcated by shale beds, which reduced their thicknesses variably from 0.61 to 6.1 m. The shale content in the sand bodies ranged from 11.00% (relatively clean) to high shale content of 88.00%. The formation also has variable porosity values, with calculated total porosity ranged as low as 10.00% to as high as 35.00%. Similarly, effective porosity values spanned between 2.00 to 24.00%. The irregular porosity values also accounted for a wide range of field average permeability estimates computed for the formation, which measured between 0.03 to 319.49 mD. Hydrocarbon saturation (Sh) in the thin lenticular sand bodies also varied from 40.00 to 78.00%. Hydrocarbon was encountered in three intervals in Ga-1, four intervals in Da-1, two intervals in Ar-1, and one interval in Ye-1. Ga-1 well encountered 30.78 m thick of hydrocarbon column in 14 thin sand lobes in Bima Sand-1, with thicknesses from 0.60 m to 5.80 m and average saturation of 51.00%, while Bima Sand-2 intercepted 45.11 m thick of hydrocarbon column in 12 thin sand lobes with an average saturation of 61.00% and Bima Sand-9 has 6.30 m column in 4 thin sand lobes. Da-1 has hydrocarbon in Bima Sand-8 (5.30 m, Sh of 58.00% in 5 sand lobes), Bima Sand-10 (13.50 m, Sh of 52.00% in 6 sand lobes), Bima Sand-11 (6.20 m, Sh of 58.00% in 2 sand lobes) and Bima Sand-12 (16.50 m, Sh of 66% in 6 sand lobes). In the Ar-1 well, hydrocarbon occurs in Bima Sand-3 (2.40 m column, Sh of 48% in a sand lobe) and Bima Sand-9 (6.0 m, Sh of 58% in a sand lobe). Ye-1 well only intersected 0.5 m hydrocarbon in Bima Sand-1 with 78% saturation. Although Bima Formation has variable saturation of hydrocarbon, mainly gas in Maiduguri, and Baga/Lake sub-basins of the research area, its highly thin serrated sand beds, coupled with very low effective porosity and permeability in part, would pose a significant exploitation challenge. The sediments were deposited in a fluvio-lacustrine environment, resulting in a very thinly laminated or serrated alternation of sand and shale beds lithofacies.

Keywords: Bima, Chad Basin, fluvio-lacustrine, lithofacies, serrated sand

Procedia PDF Downloads 172

Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

Procedia PDF Downloads 274

Authors: Elena Listo, Miguel Marchamalo

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This research studies the soil properties located in the watershed of Jabillo River in the Guanacaste province, Costa Rica. The soils are classified as Alfisols (T. Haplustalfs), in the flatter parts with grazing as Fluventic Haplustalfs or as a consequence of bad drainage as F. Epiaqualfs. The objective of this project is to define the status of the soil, to use remote sensing as a tool for analyzing the evolution of land use and determining the water balance of the watershed in order to improve the efficiency of the water collecting systems. Soil samples were analyzed from trial pits taken from secondary forests, degraded pastures, mature teak plantation, and regrowth -Tectona grandis L. F.- species developed favorably in the area. Furthermore, to complete the study, infiltration measurements were taken with an artificial rainfall simulator, as well as studies of soil compaction with a penetrometer, in points strategically selected from the different land uses. Regarding remote sensing, nearly 40 data samples were collected per plot of land. The source of radiation is reflected sunlight from the beam and the underside of leaves, bare soil, streams, roads and logs, and soil samples. Infiltration reached high levels. The majority of data came from the secondary forest and mature planting due to a high proportion of organic matter, relatively low bulk density, and high hydraulic conductivity. Teak regrowth had a low rate of infiltration because the studies made regarding the soil compaction showed a partial compaction over 50 cm. The secondary forest presented a compaction layer from 15 cm to 30 cm deep, and the degraded pasture, as a result of grazing, in the first 15 cm. In this area, the alfisols soils have high content of iron oxides, a fact that causes a higher reflectivity close to the infrared region of the electromagnetic spectrum (around 700mm), as a result of clay texture. Specifically in the teak plantation where the reflectivity reaches values of 90 %, this is due to the high content of clay in relation to others. In conclusion, the protective function of secondary forests is reaffirmed with regards to erosion and high rate of infiltration. In humid climates and permeable soils, the decrease of runoff is less, however, the percolation increases. The remote sensing indicates that being clay soils, they retain moisture in a better way and it means a low reflectivity despite being fine texture.

Keywords: alfisols, Costa Rica, infiltration, remote sensing

Procedia PDF Downloads 696

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

Procedia PDF Downloads 34

Authors: Stephen Osakue Amiandamhen, Schwaller Andreas, Martina Meincken, Luvuyo Tyhoda

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Invasive alien tree species are currently being cleared in South Africa as a result of the forest and water imbalances. These species grow wildly constituting about 40% of total forest area. They compete with the ecosystem for natural resources and are considered as ecosystem engineers by rapidly changing disturbance regimes. As such, they are harvested for commercial uses but much of it is wasted because of their form and structure. The waste is being sold to local communities as fuel wood. These species can be considered as potential feedstock for the production of phosphate bonded composites. The presence of bark in wood-based composites leads to undesirable properties, and debarking as an option can be cost implicative. This study investigates the potentials of these invasive species processed without debarking on some fundamental properties of wood-based panels. Some invasive alien tree species were collected from EC Biomass, Port Elizabeth, South Africa. They include Acacia mearnsii (Black wattle), A. longifolia (Long-leaved wattle), A. cyclops (Red-eyed wattle), A. saligna (Golden-wreath wattle) and Eucalyptus globulus (Blue gum). The logs were chipped as received. The chips were hammer-milled and screened through a 1 mm sieve. The wood particles were conditioned and the quantity of bark in the wood was determined. The binding matrix was prepared using a reactive magnesia, phosphoric acid and class S fly ash. The materials were mixed and poured into a metallic mould. The composite within the mould was compressed at room temperature at a pressure of 200 KPa. After initial setting which took about 5 minutes, the composite board was demoulded and air-cured for 72 h. The cured product was thereafter conditioned at 20°C and 70% relative humidity for 48 h. Test of physical and strength properties were conducted on the composite boards. The effect of binder formulation and fly ash content on the properties of the boards was studied using fitted response surface technology, according to a central composite experimental design (CCD) at a fixed wood loading of 75% (w/w) of total inorganic contents. The results showed that phosphate/magnesia ratio of 3:1 and fly ash content of 10% was required to obtain a product of good properties and sufficient strength for intended applications. The proposed products can be used for ceilings, partitioning and insulating wall panels.

Keywords: invasive alien tree species, phosphate bonded composites, physical properties, strength

Procedia PDF Downloads 295

Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

Procedia PDF Downloads 92

Authors: Nader Mohamed

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The Late Cretaceous deposits are well developed through-out Egypt. This is due to a ‎transgression phase associated with the subsidence caused by the neo-Tethyan rift event that ‎took place across the northern margin of Africa, resulting in a period of dominantly marine ‎deposits in the Gulf of Suez. The Late Cretaceous Nezzazat Group represents the Cenomanian, ‎Turonian and clastic sediments of the Lower Senonian. The Nezzazat Group has been divided ‎into four formations namely, from base to top, the Raha Formation, the Abu Qada Formation, ‎the Wata Formation and the Matulla Formation. The Cenomanian Raha and the Lower Senonian ‎Matulla formations are the most important clastic sequence in the Nezzazat Group because they ‎provide the highest net reservoir thickness and the highest net/gross ratio. This study emphasis ‎on Matulla formation located in the eastern part of the Gulf of Suez. The three stratigraphic ‎surface sections (Wadi Sudr, Wadi Matulla and Gabal Nezzazat) which represent the exposed ‎Coniacian-Santonian sediments in Sinai are used for correlating Matulla sediments of Ras ‎Budran field. Cutting description, petrographic examination, log behaviors, biostratigraphy with ‎outcrops are used to identify the reservoir characteristics, lithology, facies environment logs and ‎subdivide the Matulla formation into three units. The lower unit is believed to be the main ‎reservoir where it consists mainly of sands with shale and sandy carbonates, while the other ‎units are mainly carbonate with some streaks of shale and sand. Reservoir modeling is an ‎effective technique that assists in reservoir management as decisions concerning development ‎and depletion of hydrocarbon reserves, So It was essential to model the Matulla reservoir as ‎accurately as possible in order to better evaluate, calculate the reserves and to determine the ‎most effective way of recovering as much of the petroleum economically as possible. All ‎available data on Matulla formation are used to build the reservoir structure model, lithofacies, ‎porosity, permeability and water saturation models which are the main parameters that describe ‎the reservoirs and provide information on effective evaluation of the need to develop the oil ‎potentiality of the reservoir. This study has shown the effectiveness of; 1) the integration of ‎geological data to evaluate and subdivide Matulla formation into three units. 2) Lithology and ‎facies environment interpretation which helped in defining the nature of deposition of Matulla ‎formation. 3) The 3D reservoir modeling technology as a tool for adequate understanding of the ‎spatial distribution of property and in addition evaluating the unlocked new reservoir areas of ‎Matulla formation which have to be drilled to investigate and exploit the un-drained oil. 4) This ‎study led to adding a new room of production and additional reserves to Ras Budran field. ‎

Keywords: geology, oil and gas, geoscience, sequence stratigraphy

Procedia PDF Downloads 106

Authors: Alaa Ashraf Khaleel Abdallah

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Background: The global landscape has witnessed an alarming rise in armed conflicts, further devastating populations through enforced displacement, compromised infrastructure, and strained healthcare systems. In Sudan, the situation is particularly dire, with conflict exacerbating shortages in medical supplies and personnel, pushing the already fragile healthcare system into crisis, especially affecting surgical care. Initially, war impacts were significant in conflict zones like Khartoum, but since mid-April 2023, the entire country has descended into chaos. Weak monitoring and health information systems hinder accurate assessment of surgical care in conflict zones, leading to inadequate resource allocation, suboptimal care, and missed opportunities for global learning. This study investigates the impact of the Sudanese conflict on postoperative complications, exploring prevalence, types, outcomes, and psychological effects in conflict and safe areas. Methods: Conducted across 10 Sudanese states—5 in conflict zones such as Khartoum and West Darfur, and 5 in safer regions like River Nile and Kassala—this study analyzed data from 1,457 patients who underwent surgery post-April 2023. Data were collected using a pretested, mixed-mode questionnaire that incorporated elements from validated frameworks and tailored questions specific to the study's context. Hospital records and surgical logs were also used, with data analyzed via SPSS. Results: The overall prevalence of postoperative complications was 35.89%, with a higher rate in conflict zones (57.5%) compared to safe areas (26.4%). Surgical site infections predominated in conflict zones (24.7%) and higher than its prevalence in safe areas, and while fever was prevalent in safer regions even though much less compared to conflict areas, bleeding from surgical site was very frequent in conflict areas. Most patients recovered within two months at a rate higher in safe areas, but most of them required further medical or surgical management within the first month, but psychological impacts were more pronounced in conflict zones with 22.22% reported anxiety among injuries patients, and 20.6% experienced depression, 13.5% and 16.9% respectively, in those had surgeries for other medical conditions, compared to 0.22%anxiety rates and 8.1%for depression in safer regions. Risk factors included age, travel to conflict zones, access to care, delays, and comorbidities. Conclusion: Strengthening healthcare systems and ensuring accessible surgical care are critical in both conflict and safe areas. Specific attention must be given to addressing patient suffering and demographic shifts caused by armed conflict. Further research is needed to refine the predictive model for postoperative complications in conflict zones.

Keywords: postoperative complications, conflict zones, risk factors, surgical outcomes, Sudan

Procedia PDF Downloads 13

Authors: Emmanuel O. Ezim, Idowu A. Olayinka, Michael Oladunjoye, Izuchukwu I. Obiadi

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Monitoring of reservoir properties prior to well placements and production is a requirement for optimisation and efficient oil and gas production. This is usually done using well log analyses and 3-D seismic, which are often prone to errors. However, 4-D (Time-lapse) seismic, incorporating numerous 3-D seismic surveys of the same field with the same acquisition parameters, which portrays the transient changes in the reservoir due to production effects over time, could be utilised because it generates better resolution. There is, however dearth of information on the applicability of this approach in the Niger Delta. This study was therefore designed to apply 4-D seismic, well-log and geologic data in monitoring of reservoirs in the EK field of the Niger Delta. It aimed at locating bypassed accumulations and ensuring effective reservoir management. The Field (EK) covers an area of about 1200km2 belonging to the early (18ma) Miocene. Data covering two 4-D vintages acquired over a fifteen-year interval were obtained from oil companies operating in the field. The data were analysed to determine the seismic structures, horizons, Well-to-Seismic Tie (WST), and wavelets. Well, logs and production history data from fifteen selected wells were also collected from the Oil companies. Formation evaluation, petrophysical analysis and inversion alongside geological data were undertaken using Petrel, Shell-nDi, Techlog and Jason Software. Well-to-seismic tie, formation evaluation and saturation monitoring using petrophysical and geological data and software were used to find bypassed hydrocarbon prospects. The seismic vintages were interpreted, and the amounts of change in the reservoir were defined by the differences in Acoustic Impedance (AI) inversions of the base and the monitor seismic. AI rock properties were estimated from all the seismic amplitudes using controlled sparse-spike inversion. The estimated rock properties were used to produce AI maps. The structural analysis showed the dominance of NW-SE trending rollover collapsed-crest anticlines in EK with hydrocarbons trapped northwards. There were good ties in wells EK 27, 39. Analysed wavelets revealed consistent amplitude and phase for the WST; hence, a good match between the inverted impedance and the good data. Evidence of large pay thickness, ranging from 2875ms (11420 TVDSS-ft) to about 2965ms, were found around EK 39 well with good yield properties. The comparison between the base of the AI and the current monitor and the generated AI maps revealed zones of untapped hydrocarbons as well as assisted in determining fluids movement. The inverted sections through EK 27, 39 (within 3101 m - 3695 m), indicated depletion in the reservoirs. The extent of the present non-uniform gas-oil contact and oil-water contact movements were from 3554 to 3575 m. The 4-D seismic approach led to better reservoir characterization, well development and the location of deeper and bypassed hydrocarbon reservoirs.

Keywords: reservoir monitoring, 4-D seismic, well placements, petrophysical analysis, Niger delta basin

Procedia PDF Downloads 117

Authors: Adam Fheed

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Carbonate porosity can be deceptive in the aspect of hydrocarbon exploration due to pore geometry variations, which are to some extent controlled by fossils. Therefore, the main aim of this paper was to assess the dependence of pore geometry and reservoir quality on fossils. The Permian Zechstein Limestone (Ca1) carbonates from the Brońsko Reef, located on the Wolsztyn Ridge in West Poland, were examined. Seventy meters of drill cores were described along with well log examination and transmitted-light microscope research. The archival porosity-permeability data was utilized to calibrate the well logs and look for the potential petrophysical trends. Several organism assemblages were recognized in the reef. Its bottom was colonized by the branched bryozoans which were fragmented and dissolved leaving poorly connected molds. Subsequently, numerous bivalves and gastropods appeared and their shells were heavily dissolved to form huge, albeit poorly communicated caverns. Such pores were also typical for local brachiopod occurrences. Although the caverns were widespread, and probably linked to the meteoric dissolution or freshwater flushing, severe anhydrite cementation has destroyed the majority of pores. Close to the top of Ca1, near the center of the reef, the fossil-rich zone comprising fenestrate bryozoans, extremely abundant encrusting foraminifers, bivalves, brachiopods, gastropods and ostracods, was identified. The zone contained extremely frequent dissolution channels formed within former shells of foraminifers, which had previously encrusted the bryozoans. The deposition of Ca1 strata has ultimately terminated with a poorly porous and generally impermeable stromatolitic layer containing scarce fossils. In general, the permeability of the reef rocks studied turned out to be the highest under the presence of foraminifer-related channels. In such cases, it frequently approached 100 mD. The presence of channels and other pores gave the average effective porosity derived from shallow resistivity and helium porosimetry of around 16 and 18 %, respectively. The highest porosity (over 18 %), often co-occurring with relatively low permeability (chiefly below 20 mD) was noted for the bottommost zone of the reef, represented by branched bryozoans. This is probably owing to a large amount of unconnected bryozoan-related molds. It was concluded that fossils played a major role in porosity formation and controlled the pore geometry significantly. While the dissolution of bivalves and brachiopods resulted in cavernous porosity formation, numerous molds were typically related with the alteration of branched bryozoans, gastropods and ostracods. Importantly, the bendy dissolution channels after the encrusting foraminifers appeared to be decisive in improving reservoir quality – specifically when permeability is considered. Acknowledgment: The research was financed by the Polish National Science Centre’s project No. UMO-2016/23/N/ST10/00350.

Keywords: dissolution channels, fossils, Permian, porosity

Procedia PDF Downloads 85

Authors: Simon Winberg

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The landscape of professional postgraduate education is changing: the focus of these programmes is moving from preparing candidates for a life in academia towards a focus of training in expert knowledge and skills to support industry. This is especially pronounced in engineering disciplines where increasingly more complex products are drawing on a depth of knowledge from multiple fields. This connects strongly with the broader notion of Industry 4.0 – where technology and society are being brought together to achieve more powerful and desirable products, but products whose inner workings also are more complex than before. The changes in what we do, and how we do it, has a profound impact on what industry would like universities to provide. One such change is the increased demand for taught doctoral and Masters programmes. These programmes aim to provide skills and training for professionals, to expand their knowledge of state-of-the-art tools and technologies. This paper investigates one such course, namely a Software Defined Radio (SDR) Master’s degree course. The teaching support for this course had to be drawn from an existing pool of academics, none of who were specialists in this field. The paper focuses on the kind of educator, a ‘hybrid academic’, assembled from available academic staff and bolstered by research. The conceptual framework for this paper combines Activity Theory and Genre Ecology. Activity Theory is used to reason about learning and interactions during the course, and Genre Ecology is used to model building and sharing of technical knowledge related to using tools and artifacts. Data were obtained from meetings with students and lecturers, logs, project reports, and course evaluations. The findings show how the course, which was initially academically-oriented, metamorphosed into a tool-dominant peer-learning structure, largely supported by the sharing of technical tool-based knowledge. While the academic staff could address gaps in the participants’ fundamental knowledge of radio systems, the participants brought with them extensive specialized knowledge and tool experience which they shared with the class. This created a complicated dynamic in the class, which centered largely on engagements with technology artifacts, such as simulators, from which knowledge was built. The course was characterized by a richness of ‘epistemic objects’, which is to say objects that had knowledge-generating qualities. A significant portion of the course curriculum had to be adapted, and the learning methods changed to accommodate the dynamic interactions that occurred during classes. This paper explains the SDR Masters course in terms of conflicts and innovations in its activity system, as well as the continually hybridizing genre ecology to show how the structuring and resource-dependence of the course transformed from its initial ‘traditional’ academic structure to a more entangled arrangement over time. It is hoped that insights from this paper would benefit other educators involved in the design and teaching of similar types of specialized professional postgraduate taught programmes.

Keywords: professional postgraduate education, taught masters, engineering education, software defined radio

Procedia PDF Downloads 93

Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

Procedia PDF Downloads 83

Authors: Hsien-Te Lin

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The purpose of this paper is to introduce the BCFES (building carbon footprint evaluation system), which is a LCA (life cycle assessment) tool developed by the Low Carbon Building Alliance (LCBA) in Taiwan. A qualified BCFES for the building industry should fulfill the function of evaluating carbon footprint throughout all stages in the life cycle of building projects, including the production, transportation and manufacturing of materials, construction, daily energy usage, renovation and demolition. However, many existing BCFESs are too complicated and not very designer-friendly, creating obstacles in the implementation of carbon reduction policies. One of the greatest obstacle is the misapplication of the carbon footprint inventory standards of PAS2050 or ISO14067, which are designed for mass-produced goods rather than building projects. When these product-oriented rules are applied to building projects, one must compute a tremendous amount of data for raw materials and the transportation of construction equipment throughout the construction period based on purchasing lists and construction logs. This verification method is very cumbersome by nature and unhelpful to the promotion of low carbon design. With a view to provide an engineer-oriented BCFE with pre-diagnosis functions, a component input/output (I/O) database system and a scenario simulation method for building energy are proposed herein. Most existing BCFESs base their calculations on a product-oriented carbon database for raw materials like cement, steel, glass, and wood. However, data on raw materials is meaningless for the purpose of encouraging carbon reduction design without a feedback mechanism, because an engineering project is not designed based on raw materials but rather on building components, such as flooring, walls, roofs, ceilings, roads or cabinets. The LCBA Database has been composited from existing carbon footprint databases for raw materials and architectural graphic standards. Project designers can now use the LCBA Database to conduct low carbon design in a much more simple and efficient way. Daily energy usage throughout a building's life cycle, including air conditioning, lighting, and electric equipment, is very difficult for the building designer to predict. A good BCFES should provide a simplified and designer-friendly method to overcome this obstacle in predicting energy consumption. In this paper, the author has developed a simplified tool, the dynamic Energy Use Intensity (EUI) method, to accurately predict energy usage with simple multiplications and additions using EUI data and the designed efficiency levels for the building envelope, AC, lighting and electrical equipment. Remarkably simple to use, it can help designers pre-diagnose hotspots in building carbon footprint and further enhance low carbon designs. The BCFES-LCBA offers the advantages of an engineer-friendly component I/O database, simplified energy prediction methods, pre-diagnosis of carbon hotspots and sensitivity to good low carbon designs, making it an increasingly popular carbon management tool in Taiwan. To date, about thirty projects have been awarded BCFES-LCBA certification and the assessment has become mandatory in some cities.

Keywords: building carbon footprint, life cycle assessment, energy use intensity, building energy

Procedia PDF Downloads 139

Authors: Jenifer Alam, Rima Chatterjee

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Upper Assam sedimentary basin is one of the oldest commercially producing basins of India. Being in a tectonically active zone, estimation of tectonic strain and stress magnitudes has vast application in hydrocarbon exploration and exploitation. This East North East –West South West trending shelf-slope basin encompasses the Bramhaputra valley extending from Mikir Hills in the southwest to the Naga foothills in the northeast. Assam Shelf lying between the Main Boundary Thrust (MBT) and Naga Thrust area is comparatively free from thrust tectonics and depicts normal faulting mechanism. The study area is bounded by the MBT and Main Central Thrust in the northwest. The Belt of Schuppen in the southeast, is bordered by Naga and Disang thrust marking the lower limit of the study area. The entire Assam basin shows low-level seismicity compared to other regions of northeast India. Pore pressure (PP), vertical stress magnitude (SV) and horizontal stress magnitudes have been estimated from two wells - N1 and T1 located in Upper Assam. N1 is located in the Assam gap below the Bramhaputra river while T1, lies in the Belt of Schuppen. N1 penetrates geological formations from top Alluvial through Dhekiajuli, Girujan, Tipam, Barail, Kopili, Sylhet and Langpur to the granitic basement while T1 in trusted zone crosses through Girujan Suprathrust, Tipam Suprathrust, Barail Suprathrust to reach Naga Thrust. Normal compaction trend is drawn through shale points through both wells for estimation of PP using the conventional Eaton sonic equation with an exponent of 1.0 which is validated with Modular Dynamic Tester and mud weight. Observed pore pressure gradient ranges from 10.3 MPa/km to 11.1 MPa/km. The SV has a gradient from 22.20 to 23.80 MPa/km. Minimum and maximum horizontal principal stress (Sh and SH) magnitudes under isotropic conditions are determined using poroelastic model. This approach determines biaxial tectonic strain utilizing static Young’s Modulus, Poisson’s Ratio, SV, PP, leak off test (LOT) and SH derived from breakouts using prior information on unconfined compressive strength. Breakout derived SH information is used for obtaining tectonic strain due to lack of measured SH data from minifrac or hydrofracturing. Tectonic strain varies from 0.00055 to 0.00096 along x direction and from -0.0010 to 0.00042 along y direction. After obtaining tectonic strains at each well, the principal horizontal stress magnitudes are calculated from linear poroelastic model. The magnitude of Sh and SH gradient in normal faulting region are 12.5 and 16.0 MPa/km while in thrust faulted region the gradients are 17.4 and 20.2 MPa/km respectively. Model predicted Sh and SH matches well with the LOT data and breakout derived SH data in both wells. It is observed from this study that the stresses SV>SH>Sh prevailing in the shelf region while near the Naga foothills the regime changes to SH≈SV>Sh area corresponds to normal faulting regime. Hence this model is a reliable tool for predicting stress magnitudes from well logs under active tectonic regime in Upper Assam Basin.

Keywords: Eaton, strain, stress, poroelastic model

Procedia PDF Downloads 216

Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

Abstract:

In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

Procedia PDF Downloads 48

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 68