Search results for: geochemical anomaly

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

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Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

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The present work is an organic geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a mixed origin (type II and III), as indicated by the relatively high values of hydrogen index. This origin is confirmed by the C29 Steranes abundance and also by tricyclic terpanes C19/(C19+C23) and tetracyclic terpanes C24/(C24+C23) ratios, that suggest a marine environment of deposit with high plants contribution. We have demonstrated that the heterogeneity of organic matter between the marine aspect, confirmed by the presence of foraminifera, and the continental contribution, is the result of an episodic anomaly in relation to the sequential stratigraphy. Given that the study area is defined as an outer platform forming a transition zone between a stable continental domain to the south and a deep basin to the north, we have explained the continental contribution by successive forced regressions, having blocked the albian transgression, allowing the installation of the lowstand system tracts. This aspect is represented by the incised valleys filling, in direct contact with the pelagic and deep sea facies. Consequently, the Fahdene Formation, in the Kef-Tedjerouine area, consists of transgressive system tracts (TST) brutally truncated by extras of continental progradation; resulting in a mixed influence deposition having retained a heterogeneous organic material.

Keywords: molecular geochemistry, biomarkers, forced regression, deposit environment, mixed origin, Northern Tunisia

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Authors: Tanu Sharma, Bikramjit Singh Bajwa, Inderpreet Kaur

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Monitoring of groundwater in Tarn-Taran, Bathinda, Faridkot and Mansa districts of Punjab state, India is essential where this freshwater resource is being over-exploited causing quality deterioration, groundwater depletion and posing serious threats to residents. The present integrated study was done to appraise quality and suitability of groundwater for drinking/irrigation purposes, hydro-geochemical characteristics, source identification and associated health risks. In the present study, groundwater of various districts of Punjab state was found to be heavily contaminated with As followed by U, thus posing high cancerous risks to local residents via ingestion, along with minor contamination of Fe, Mn, Pb and F−. Most health concerns in the study region were due to the elevated concentrations of arsenic in groundwater with average values of 130 µg L-1, 176 µg L-1, 272 µg L-1 and 651 µg L-1 in Tarn-Taran, Bathinda, Faridkot and Mansa districts, respectively, which is quite high as compared to the safe limit as recommended by BIS i.e. 10 µg L-1. In Tarn-Taran, Bathinda, Faridkot and Mansa districts, average uranium contents were found to be 37 µg L-1, 88 µg L-1, 61 µg L-1 and 104 µg L-1, with 51 %, 74 %, 61 % and 71 % samples, respectively, being above the WHO limit of 30 µg L-1 in groundwater. Further, the quality indices showed that groundwater of study region is suited for irrigation but not appropriate for drinking purposes. Hydro-geochemical studies revealed that most of the collected groundwater samples belonged to Ca2+ - Mg2+ - HCO3- type showing dominance of MgCO3 type which indicates the presence of temporary hardness in groundwater. Rock-water reactions and reverse ion exchange were the predominant factors for controlling hydro-geochemistry in the study region. Dissolution of silicate minerals caused the dominance of Na+ ions in the aquifers of study region. Multivariate statistics revealed that along with geogenic sources, contribution of anthropogenic activities such as injudicious application of agrochemicals and domestic waste discharge was also very significant. The results obtained abolished the myth that uranium is only root cause for large number of cancer patients in study region as arsenic and mercury were also present in groundwater at levels that were of health concern to groundwater.

Keywords: uranium, trace elements, multivariate data analysis, risk assessment

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

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Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

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The present work is an organo-geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a planktonic marine origin (type II), as indicated by the relatively high values of hydrogen index. Tmax values are in the range 440°C and attest a thermal stage of the oil window beginning. Mineralogical study found the existence of macro and micro fractures that are parallel to rock stratification or oblique with a high density. Fill standpoint, the major component of the mineralized veins is the fibrous calcite with bitumen traces. The composition of these fractures is mainly due to the availability of chemical elements scattered in the surrounding rock. As for the origin of these fractures, we assume that fluid pressure processes are heavily involved, together with the regional compressional tectonic stress regime. The Fahdene Formation has a great importance in conventional oil development as a potential source rock, and even in terms of unconventional oil exploitation through the intense fracturing allowing the percolation of gas shale and facilitating its exploitation.

Keywords: fluid pressure, fracturation, oil exploration, organic matter

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Authors: Chongwain G. Mbzighaa, Christopher M. Agyingi, Josepha-Forba-Tendo

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Background and aim: Sedimentological, geochemical and petrographic studies were carried out on carbonate-bearing argillites outcropping at the southeastern flank of Mount Cameroon (Likomba) to determine the lithofacies and their associations, major element geochemistry and mineralogy. Methods: Major elements of the rocks were analyzed using XRF technique. Thermal analysis and thin section studies were carried out accompanied with the determination of insoluble components of the carbonates. Results: The carbonates are classed as biomicrites with siderite being the major carbonate mineral. Clay, quartz and pyrite constitute the major insoluble components of these rocks. Geochemical results depict a broad variation in their concentrations with silica and iron showing the highest concentrations and sodium and manganese with the least concentrations. Two factors were revealed with the following elemental associations, Fe2O3-MgO-Mn2O3 (72.56 %) and TiO2-SiO2-Al2O3-K2O (23.20%) indicating both Fe-enrichment, the subsequent formation of the siderite and the contribution of the sediments to the formation of these rocks. Conclusion: The rocks consist of cyclic iron-rich carbonates alternating with sideritic-shales and might have been formed as a result of variations in the sea conditions as well as variation in sediment influx resulting from transgression and regression sequences occurring in a shallow to slightly deep marine environments.

Keywords: sedimentology, geochemistry, petrography, iron carbonates, Likomba

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Authors: Hassan Farhan Alfugha

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the cenozoic volcanism in westt central jordan which show homohgenous lava from upper mantle.es represented by basaltic scoria cones and flows and covers approximately 10 km. fourtten nephelinitic rock samples were collected at jurf ed-darawish volcanism to analyze major minor and trace elements by using XRF.. geochemical parameters of these samp;es such as MG/MG+FE+2, the ratio range from 0.41 to 0.45 and high ti contents 3.09-3.28wt % indicate that the corresponding magmas are nearly of primary origin . this magma show low variable abundances of compatible and incompatible trace elements reflecting a homogenous source. the studied volcanic rocks, which are mainly nephlinites, belong to the alkaline rocks series containing 4.38-5.95wt% alkali oxides they are usually undersaturated in regard it the silica content, which ranges between 39.88-41.50wt.%.value compared to other jordanien basaltic rocks majorminor and trace elementes data as well as mantel xenoliths entrained in the volcanic rocks are spinel iherzolites that suggest the lithospheric mantle as the source for the pleistocene volcanism these xenoliths resided at shallow mantle depths (45 km ) because a geothermobarometric analysis yielded p-t conditions close to 15 kbar and 1100c the mantle nodules did not equilibrate with the melts indicating a fast transport from the mantle to the surface and a mgma >65 km deeper source area of the melts.

Keywords: nephelinite plestocene western central jordan, western central jordan, volcano in western central jordan, central jordan

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Authors: Esra Ece Var

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Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

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Authors: Mihai I. Sturza, Laura T. Corredor, Kaustuv Manna, Gizem A. Cansever, Tushar Dey, Andrey Maljuk, Olga Kataeva, Sabine Wurmehl, Anja Wolter, Bernd Buchner

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Recently, the iridate double perovskite Sr₂YIrO₆ has attracted considerable attention due to the report of unexpected magnetism in this Ir⁵⁺ material, in which according to the Jeff model, a non-magnetic ground state is expected. Structural, magnetic and thermodynamic investigations of Sr₂YIrO₆ and Ba2YIrO6 single crystals, with emphasis on the temperature and magnetic field dependence of the specific heat will be presented. The single crystals were grown by using SrCl₂ and BaCl₂ as flux. Single-crystal X-ray diffraction measurements performed on several crystals from different preparation batches showed a high quality of the crystals, proven by the good internal consistency of the data collected using the full-sphere mode and an extremely low R factor. In agreement with the expected non-magnetic ground state of Ir⁵⁺ (5d4) in these iridates, no magnetic transition is observed down to 430 mK. Moreover, our results suggest that the low-temperature anomaly observed in the specific heat is not related to the onset of long-range magnetic order. Instead, it is identified as a Schottky anomaly caused by paramagnetic impurities present in the sample, of the order of

Keywords: double perovskites, iridates, self-flux grown synthesis, spin-orbit coupling

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

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Authors: Iklass Hamaili, Fehdi Chemseddine

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Morphostructural, hydrogeological and hydrochemical approaches were applied in this study to characterize the groundwater system of Hammamet Plain, Eastern part of Algeria and its potential for exploitation. The analysis of the fractures in several Mountains forming the natural boundaries of Hammamet plain, with faults of markedly different sizes and joints measured at 21 stations, demonstrate the presence of two principal directions of fractures (NNW-SSE and NNE-SSW). From a hydrogeological standpoint, these two mountains constitute a unit limited by faults-oriented ENE-WSW, NNW-SSE and NNE-SSW. Specifically, fractures of the latter two directions influence the compartmentalization and the hydrogeological functioning of this unit. According to the degree of fracturing and/or karstification, two basic types of aquiferous behavior have been distinguished: fissured aquifer (Essen Mountain and Troubia Mountain), and porous aquifer (Hammamet basin). After sampling and measurement operations, the quantity of chemical components was determined. Thus, the study of the hydrochemical characteristics of this groundwater shows on Piper’s diagram that the majority of them are mainly HCO₃- and Ca₂+ water types. The ionic speciation and mineral dissolution/precipitation were calculated by PHREEQC package software. The chemical composition of the water is influenced by the dissolution and/or precipitation processes during the water-rock interaction and by the cationic exchange reactions between groundwater and alluvial sediments. The high content of CO₂ in the water samples suggests that they circulate in a geochemical opened system.

Keywords: aquifer, hydrogeology, hydrochemistry, Hammamet, Tebessa, Algeria

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Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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Authors: Naresh Kumar, Radhika Sharma, A. K. Singh

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Acid plutonic rocks from the Khanak and Devsar areas of southwestern Haryana were investigated to understand their geochemical and petrogenetic characteristics and tectonic environments. Three dominant rock types (grey, grayish green and pink granites) are the principal geochemical features of Khanak and Devsar areas which reflect the dependencies of their composition on varied geological environment during the anorogenic magmatism. These rocks are enriched in SiO₂, Na₂O+K₂O, Fe/Mg, Rb, Zr, Y, Th, U, REE (Rare Earth Elements) enriched and depleted in MgO, CaO, Sr, P, Ti, Ni, Cr, V and Eu and exhibit a clear affinity to the within-plate granites that were emplaced in an extensional tectonic environment. Chondrite-normalized REE patterns show enriched LREE (Light Rare Earth Elements), moderate to strong negative Eu anomalies and flat heavy REE and grey and grayish green is different from pink granite which is enriched by Rb, Ga, Nb, Th, U, Y and HREE (Heavy Rare Earth Elements) concentrations. The composition of parental magma of both areas corresponds to mafic source contaminated with crustal materials. Petrogenetic modelling suggest that the acid plutonic rocks might have been generated from a basaltic source by partial melting (15-25%) leaving a residue with 35% plagioclase, 25% alkali feldspar, 25% quartz, 7% orthopyroxene, 5% biotite and 3% hornblende. Granites from both areas might be formed from different sources with different degree of melting for grey, grayish green and pink granites.

Keywords: A-type granite, anorogenic, Malani igneous suite, Khanak and Devsar

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Authors: Tugbanur Ozen Balaban, Gultekin Tarcan, Unsal Gemici, Mumtaz Colak, I. Hakki Karamanderesi

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Buyuk Menderes Graben is located in the Western Anatolia (Turkey). The graben has become the largest industrial and agricultural area with a total population exceeding 3.000.000. There are two big cities within the study areas from west to east as Aydın and Denizli. The study area is very rich with regard to cold ground waters and thermal waters. Electrical production using geothermal potential has become very popular in the last decades in this area. Buyuk Menderes Graben is a tectonically active extensional region and is undergoing a north–south extensional tectonic regime which commenced at the latest during Early Middle Miocene period. The basement of the study area consists of Menderes massif rocks that are made up of high-to low-grade metamorphics and they are aquifer for both cold ground waters and thermal waters depending on the location. Neogene terrestrial sediments, which are mainly composed by alluvium fan deposits unconformably cover the basement rocks in different facies have very low permeability and locally may act as cap rocks for the geothermal systems. The youngest unit is Quaternary alluvium which is the shallow regional aquifer consists of Holocene alluvial deposits in the study area. All the waters are of meteoric origin and reflect shallow or deep circulation according to the 8O, 2H and 3H contents. Meteoric waters move to deep zones by fractured system and rise to the surface along the faults. Water samples (drilling well, spring and surface waters) and local seawater were collected between 2010 and 2012 years. Geochemical modeling was calculated distribution of the aqueous species and exchange processes by using PHREEQCi speciation code. Geochemical analyses show that cold ground water types are evolving from Ca–Mg–HCO3 to Na–Cl–SO4 and geothermal aquifer waters reflect the water types of Na-Cl-HCO3 in Aydın. Water types of Denizli are Ca-Mg-HCO3 and Ca-Mg-HCO3-SO4. Thermal water types reflect generally Na-HCO3-SO4. The B versus Cl rates increase from east to west with the proportion of seawater introduced into the fresh water aquifers and geothermal reservoirs. Concentrations of some elements (As, B, Fe and Ni) are higher than the tolerance limit of the drinking water standard of Turkey (TS 266) and international drinking water standards (WHO, FAO etc).

Keywords: Buyuk Menderes, isotope chemistry, geochemical modelling, water quality

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Khawla Askri, Mohamed Haythem Msaddek, AbdelAziz Sebei

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Climate change combined with the increase in anthropogenic activities will affect coastal groundwater systems around the world and, more particularly, the Cap Bon region in the North East of Tunisia. This study aims to study the impact of climate change and human stress on the salinization and quantification of groundwater in the Wadi Chiba watershed. In this regard, a hydro-climatological study and a hydrogeological study were carried out based on the characterization of the aquifer system of the eastern coast at the level of the watershed of Wadi Chiba in order to seek to identify, first of all, the degradation of the state of the aquifer on the quantitative level by the study of the piezometric and its evolution over time. Secondly, we sought to identify the degradation of the state of the aquifer qualitatively by using the geochemical method, in particular the major elements, to assess the mineralization of the aquifer water and understand its hydrogeochemical functioning. The study of the Na + / Cl- and Ca2 + / Mg2 + chemical relationships confirmed the presence of a marine intrusion downstream of the Wadi Chiba watershed northeast of Cap-Bon accompanied by a piezometric depression. For this purpose, we proceeded to: 1) Mapping of both piezometric data and salinity. 2) The interpretation of the mapping results. 3)Identification of the origin of the localized deterioration in the quality of the aquifer water. Finally, the analysis of the results showed that the scarcity of water is already forcing human actions in the Chiba watershed due to the irrigation of agricultural lands and the overexploitation of the water table in the study area.

Keywords: climate change, human activities, water table, Wadi Chiba watershed, piezometric depression, marine intrusion

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Authors: Dalal Sadeqi

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Groundwater is an important component of Kuwait’s water resources. Although limited in quantity and often poor in quality, the significance of this natural source of water cannot be overemphasized. Recharge of groundwater in Kuwait occurs during periodical storm events, especially in open desert areas. Runoff water dissolves accumulated surficial meteoric salts and subsequently leaches them into the groundwater following a period of evaporative enrichment at or near the soil surface. Geochemical processes governing groundwater recharge vary in time and space. Stable isotope (18O and 2H) and geochemical signatures are commonly used to gain some insight into recharge processes and groundwater salinization mechanisms, particularly in arid and semiarid regions. This article addresses the mechanism used in identifying and characterizing the main water shed areas in Kuwait using stable isotopes in an attempt to determine favorable groundwater recharge sites in the country. Stable isotopes of both rainwater and groundwater were targeted in different hydrogeological settings. Additionally, data and information obtained from subsurface logs in the study area were collected and analyzed to develop a better understanding of the lateral and vertical extent of the groundwater aquifers. Geographic Information System (GIS) and RockWorks 3D modelling software were used to map out the hydrogeomorphology of the study area and the subsurface lithology of the investigated aquifers. The collected data and information, including major ion chemistry, isotopes, subsurface characteristics, and hydrogeomorphology, were integrated in a GIS platform to identify and map out suitable natural recharge areas as part of an integrated water resources management scheme that addresses the challenges of the sustainability of the groundwater reserves in the country.

Keywords: scarcity, integrated, recharge, isotope

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Authors: Aldilla Damayanti Purnama Ratri, Hendri Subakti, Buldan Muslim

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Ionosphere’s anomalies as an effect of earthquake activity is a phenomenon that is now being studied in seismo-ionospheric coupling. Generally, variation in the ionosphere caused by earthquake activity is weaker than the interference generated by different source, such as geomagnetic storms. However, disturbances of geomagnetic storms show a more global behavior, while the seismo-ionospheric anomalies occur only locally in the area which is largely determined by magnitude of the earthquake. It show that the earthquake activity is unique and because of its uniqueness it has been much research done thus expected to give clues as early warning before earthquake. One of the research that has been developed at this time is the approach of seismo-ionospheric-coupling. This study related the state in the lithosphere-atmosphere and ionosphere before and when earthquake occur. This paper choose the total electron content in a vertical (VTEC) in the ionosphere as a parameter. Total Electron Content (TEC) is defined as the amount of electron in vertical column (cylinder) with cross-section of 1m2 along GPS signal trajectory in ionosphere at around 350 km of height. Based on the analysis of data obtained from the LAPAN agency to identify abnormal signals by statistical methods, obtained that there are an anomaly in the ionosphere is characterized by decreasing of electron content of the ionosphere at 1 TECU before the earthquake occurred. Decreasing of VTEC is not associated with magnetic storm that is indicated as an earthquake precursor. This is supported by the Dst index showed no magnetic interference.

Keywords: earthquake, DST Index, ionosphere, seismoionospheric coupling, VTEC

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Authors: Ghulam Sohail, Christopher Hawkes

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Pakistan has been facing a growing energy crisis for the last decade, and the government is seeking new horizons for increasing oil and gas production to reduce the gap between supply and demand. Recent developments in technologies to produce natural gas from shales at economical rates has unlocked new horizons for hydrocarbon exploration and development throughout the world. Operating companies in the U.S.A. and Canada have been particularly successful at producing shale gas, so comparing against the properties of shale gas reservoirs in these countries is used for an initial assessment of prospective shale gas reservoirs in other parts of the world. In this study, selected source rocks of Pakistan are evaluated for their shale gas potential using analogs selected from various North American shales for which data have been published. Published data for Pakistani shales were compiled, then assessed and supplemented through consultation with industry professionals. Pakistani formations reviewed are the Datta (shaly sandstone), Hangu (sandy shale), Patala (sandy shale), Ranikot (shaly sandstone), Sembar (sandy shale) and Lower Goru (shaly sandstone) formations, all of which are known source rocks in the Indus Basin. For this study, available geological, geochemical, petrophysical and elastic parameters have been investigated and are correlated specifically with the eight most active shale gas plays of the U.S.A., while data for other North American shale gas plays are used for general discussion on prospective Pakistani shales. The results show that the geological and geochemical parameters of all the Pakistani shales reviewed in this work are promising regarding their shale gas. However, more petrophysical and geomechanical data are required before conclusions on economic production from these shales can be made with confidence.

Keywords: Canada shale gas, Indus Basin, Pakistani shales, U.S.A shale gas

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Authors: Anacletus Ogbunkwu

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It is very disheartening that fake news or inaccurate information spread like wide fire and even with greater speed than fact based news/information. The peak of this anomaly is manifest in information management on the Corona virus pandemic, political/leadership based information, ethnic bigotry, unwarranted panics, false alarms, religious fanaticism, and business moguls in their advertorials, comedies, etc. This ugly situation has left Nigeria and her citizens with emotional trauma, unguided agitations, incessant tribal wars, lost of life and property, widened disunity among Nigerian ethnic and religious groups, amplified insecurity, aided election violence, etc. Unfortunately, among the major driving factors to this misinformation and conspiracy are the official/government and private news agencies, gossip, comedians, and social media handles such as; facebook, twitter, whatsapp, instagram, and online news agencies, etc. Thus this paper examines the impact of misinformation here referred to as infodemic. Also, it studies the epistemic effect of misinformation on the citizens of Nigeria in order to find ways of abating this anomaly for a better society. The methods of exposition and hermeneutics will be used in order to gain in-depth study of the details of infodemic in Nigeria and to offer philosophical analysis/interpretation of data as gathered, respectively. This paper concludes that misinformation or fake news has a perilous effect of epistemic mistrust to Nigeria and her citizens; hence infodemic is a cog in the wheel of National progress.

Keywords: nigeria, infodemic, language, media, news, progress

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Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Barbora Svechova, Monika Licbinska

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Geochemical modeling of mineralogical changes of various materials in contact with an aqueous solution is an important tool for predicting the processes and development of given materials at the site. The modeling focused on the mutual interaction of groundwater at the contact with the rock mass and its subsequent influence on concrete structures. The studied locality is located in Slovakia in the area of the Liptov Basin, which is a significant inter-mountain lowland, which is bordered on the north and south by the core mountains belt of the Tatras, where in the center the crystalline rises to the surface accompanied by Mesozoic cover. Groundwater in the area is bound to structures with complicated geological structures. From the hydrogeological point of view, it is an environment with a crack-fracture character. The area is characterized by a shallow surface circulation of groundwater without a significant collector structure, and from a chemical point of view, groundwater in the area has been classified as calcium bicarbonate with a high content of CO2 and SO4 ions. According to the European standard EN 206-1, these are waters with medium aggression towards the concrete. Three rock samples were taken from the area. Based on petrographic and mineralogical research, they were evaluated as calcareous shale, micritic limestone and crystalline shale. These three rock samples were placed in demineralized water for one month and the change in the chemical composition of the water was monitored. During the solution-rock interaction there was an increase in the concentrations of all major ions, except nitrates. There was an increase in concentration after a week, but at the end of the experiment, the concentration was lower than the initial value. Another experiment was the interaction of groundwater from the studied locality with a concrete structure. The concrete sample was also left in the water for 1 month. The results of the experiment confirmed the assumption of a reduction in the concentrations of calcium and bicarbonate ions in water due to the precipitation of amorphous forms of CaCO3 on the surface of the sample.Vice versa, it was surprising to increase the concentration of sulphates, sodium, iron and aluminum due to the leaching of concrete. Chemical analyzes from these experiments were performed in the PHREEQc program, which calculated the probability of the formation of amorphous forms of minerals. From the results of chemical analyses and hydrochemical modeling of water collected in situ and water from experiments, it was found: groundwater at the site is unsaturated and shows moderate aggression towards reinforced concrete structures according to EN 206-1a, which will affect the homogeneity and integrity of concrete structures; from the rocks in the given area, Ca, Na, Fe, HCO3 and SO4. Unsaturated waters will dissolve everything as soon as they come into contact with the solid matrix. The speed of this process then depends on the physicochemical parameters of the environment (T, ORP, p, n, water retention time in the environment, etc.).

Keywords: geochemical modeling, concrete , dissolution , PHREEQc

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Authors: Ayten Bakhtiyar Khasayeva

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Lower Kura depression is a part of the South Caspian Basin (SCB), located between the folded regions of the Greater and Lesser Caucasus. The region is characterized by thick sedimentary cover 22 km (SCB up to 30 km), high sedimentation rate, low geothermal gradient (average value corresponds to 2 °C / 100m). There is Quaternary, Pliocene, Miocene and Oligocene deposits take part in geological structure. Miocene and Oligocene deposits are opened by prospecting and exploratory wells in the areas of Kalamaddin and Garabagli. There are 25 mud volcanoes within the territory of the Lower Kura depression, which are the unique source of information about hydrocarbons contenting great depths. During the wells data research, solid erupted products and mud volcano fluids, and according to the geological and thermal characteristics of the region, it was determined that the main phase of the hydrocarbon generation (MK1-AK2) corresponds to a wide range of depths from 10 to 14 km, which corresponds to the Pliocene-Miocene sediments, and to the "oil and gas windows" according to the intended meaning of R0 ≈ 0,65-0,85%. Fluids of mud volcanoes comprise by the following phases - gas, water. Gas phase consists mainly of methane (99%) of heavy hydrocarbons (С2+ hydrocarbons), CO2, N2, inert components He, Ar. The content of the С2+ hydrocarbons in the gases of mud volcanoes associated with oil deposits is increased. Carbon isotopic composition of methane for the Lower Kura depression varies from -40 ‰ to -60 ‰. Water of mud volcanoes are represented by all four genetic types. However the most typical types of water are HCN type. According to the Mg-Li geothermometer formation of mud waters corresponds to the temperature range from 20 °C to 140 °C (PC2). The solid product emissions of mud volcanoes identified 90 minerals and 30 trace elements. As a result geochemical investigation, thermobaric and geological conditions, zone oil and gas generation - the prospect of the Lower Kura depression is projected to depths greater than 10 km.

Keywords: geology, geochemistry, mud volcanoes, petroleum potential

Procedia PDF Downloads 366

Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

Abstract:

Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

Procedia PDF Downloads 288

Authors: Elhadi Nasr, Ibrahim Ramadan

Abstract:

Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

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Authors: Sawsen Jarray, Tahani Hallek, Mabrouk Montacer

Abstract:

The tectonically damaged terrain in Tunisia's Northwest is seen in the country's numerous oil leaks. Finding a genetic link between these oil seeps and the area's putative source rocks is the goal of this investigation. Here, we use aliphatic biomarkers assessed by GC-MS to describe the organic geochemical data of 18 oil seeps samples and 4 source rocks (M'Cherga, Fahdene, Bahloul, and BouDabbous). In order to establish correlations between oil and oil and oil and source rock, terpanes, hopanes, and steranes biomarkers were identified. The source rocks under study were deposited in a marine environment and were suboxic, with minor signs of continental input for the M'Cherga Formation. There is no connection between the Fahdene and Bahloul source rocks and the udied oil seeps. According to the biomarkers C27 18-22,29,30trisnorneohopane (Ts) and C27 17-22,29,30-trisnorhopane (Tm), these source rocks are mature and have reached the oil window. Regarding oil seeps, geochemical data indicate that, with the exception of four samples that showed some continental markings, the bulk of samples were deposited in an open marine environment. These most recent samples from oil seeps have a unique lithology (marl) that distinguishes them from the others (carbonate). There are two classes of oil seeps, according to statistical analysis of relationships between oil and oil and oil and source rocks. The first comprised samples that showed a positive connection with carbonate-lithological and marine-derived BouDabbous black shales. The second is a result of M'Cherga source rock and is made up of oil seeps with remnants of the terrestrial environment and a lithology with a marl trend. The Fahdene and Bahloul source rocks have no connection to the observed oil seeps. There are two different types of hydrocarbon spills depending on their link to tectonic deformations (oil seeps) and outcropping mature source rocks (oil impregnations), in addition to the existence of two generations of hydrocarbon spills in Northwest Tunisia (Lower Cretaceous/Ypresian).

Keywords: petroleum seeps, source rocks, biomarkers, statistic, Northern Tunisia

Procedia PDF Downloads 69