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A plot of the hydrocarbon yield (S2) versus the total organic carbon (TOC) showing organic matter richness and potentiality. The red circle defines the miss-plotted sample (El Diasty, 2015), whereas the red arrow refers to its proper position.
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The petroliferous province of the Western Desert comprises several sedimentary basins with different hydrocarbon potentiality and production capability. The middle Jurassic Khatatba Formation was proved a potential source rock in some basins and active/effective in others. The current study aims to give a comprehensive assessment and evaluation of...
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Context 1
... minimum required TOC value for a clastic (shale) source rock to be effective is 0.5 wt% (Tissot and Welte, 1984). Nevertheless, source rocks of TOC 1 wt% have been assigned poor to fair (Peters and Cassa, 1994). The measured TOC values range between 1 and 9 wt% that document a good-excellent source rock (Fig. ...
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Different parts of the Lower Cretaceous Alam El Bueib (AEB) and the Jurassic Khatatba source and reservoir rock units in the Faghur basin, like in other basins in the north Western Desert, act as hydrocarbon sources and reservoirs. In the present study, well-log data from five wells in Phiops field and geochemical data from the Neith S-2X well from...
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Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty. Though, attaining these parameters, for instance total organic carbon (TOC), volatile and residual hydrocarbon (S1 & S2) has a challenge for geologists due to high cost and time consumption. Therefore, addressing this issue has become an interesting subject f...
The evaluation of the exploratory potential for shale oil/shale gas of a source rock involves the characterization of three key factors: existence of high TOC, adequate maturity and susceptibility to fracking. Additional factors such as depositional and geological control over the distribution of organic matter in the source rock should also be inv...
Our analysis of a comprehensive well log database and complementary mineralogical and geochemical information indicates that the risk for Upper Jurassic shales on the Norwegian Continental Shelf (NCS) to permit severe leakage of hydrocarbons from the reservoir is generally low, even in the case of substantial uplift. The content of brittle minerals...
The office U.S. Energy Information Administration (EIA) has suggested significant volumes of hydrocarbon resources in unconventional Shale type reservoirs, which happens to be very interesting nowadays. The complexity of these reservoirs, along with the high level of risk during the exploration stage, and the lack of laboratory data, are challengin...
Citations
... Additionally, it involves studying the chemical composition of the rocks for hydrocarbon exploration. Techniques in this method include Rock-Evaluation pyrolysis, Gas Chromatography-Mass Spectrometry (GC-MS), and elemental analysis [11]. On the other hand, non-geochemical analysis of source rocks involves techniques like petrography, well-log analysis, and seismic data interpretations, respectively [12]. ...
Machine Learning methods have shown significance in automating the prediction of Total organic carbon (TOC) for determining source rock potential in oil and gas exploration. Higher TOC contents could indicate greater potential for oil and gas generation. Making accurate TOC predictions, therefore, is crucial in measuring hydrocarbon deposits for a prospective geological formation. Automating this procedure can save time and resources when compared to conventional geochemical methods. In this study, we explore machine learning methods on a Frontier-Basin well-log data for TOC Prediction. Firstly, we employ feature selection methods to ensure optimal feature usage in regression and classification tasks. Additionally, we compare several supervised Machine Learning methods including Logistic Regression, Decision Tree, K-Nearest Neighbor, Gradient Boosting , and Naive Bayes Methods to categorize the quality of TOC using its defined standard ranges on the well-log data of Kolmani River 2 and 3, respectively. Furthermore, Random Forest method was utilised for the regression task on both data. A 5 fold nested cross validation was utilised for both classification and regression task. We show an exploratory analysis and the prospect of using Machine Learning methods to effectively classify TOC distribution using continuous well log data. Results show that Machine Learning methods are efficient for TOC prediction for 979-8-3503-7565-7/24/$31.00 ©2024 IEEE non-geochemical approaches. The regression analysis shows an acceptable R 2 value of 0.62 and 0.76 for the respective well-logs with an MSE score of 0.05 and 0.07, respectively. For the classification task, evaluation metrics including F1 score, Precision, Accuracy, and Recall were investigated for the different ML classification methods, and Naive Bayes' was concluded to outperform others using standard metrics.
... Nevertheless, this basin has received little attention with respect to its hydrocarbon potential. In addition, most of the hydrocarbon investigations embraced mostly the conventional organic geochemical assessment methods (Metwalli and Pigott, 2005;Shalaby et al., 2011;Shalaby et al., 2014;El Nady et al., 2016;Ahmed and Hassan, 2019;Lotfy et al., 2020;El Dally, et al., 2022). In these studies, understanding of the controlling factors responsible for the accumulation and preservation of organic matter is missing (e.g., Galloway, 1989;Van Wagoner, 1995;Tyson, 1996;Deaf and Tahoun, 2018;Jong, 2019;Deaf, 2021). ...
Integrated organic petrographic and geochemical analyses were made on organic-rich marine carbonate and mixed clastic-carbonate rocks of Middle–Late Jurassic and Early Cretaceous age from the Shushan Basin, Egypt to evaluate their hydrocarbon potential. Analyses allowed the identification of depositional settings, paleoclimate, and three third order genetic stratigraphic sequences (SQ) with deposits assigned to highstand (HST), lowstand (LST) and transgressive systems tracts (TST). Deposition of the source rocks in the rifting Shushan Basin resulted from the interaction between Neotethyan sea level changes, tectonic, and climate. The good reducing conditions developed during the Neotethyan Middle–Late Jurassic (Bajocian–Kimmeridgian) second order sea level rises and the climatically induced carbonate sedimentation resulted in the deposition of the organic-rich carbonates of the Khatatba Formation (SQ 1, early–middle TST) in inner–middle shelf settings under anoxic–dysoxic conditions. The Late Jurassic (late Kimmeridgian) uplifting resulted in the deposition of the organic-lean mixed clastic–carbonate strata of the Masajid Formation (SQ 1, latest TST) in the same shelfal and reducing conditions, which experienced a notable dilution of organic matter. The late TST deposits of SQ 1 are good to very good oil-producing source rocks, where they show average good to very good generative potential of late mature (late oil-to early wet gas-window) highly oil-prone organic matter. The Early Cretaceous (Valanginian–Albian) uplifting associated with the rifting of the Shushan Basin overprinted the Neotethyan late Valanginian–Hauterivian second order sea level rises, Aptian second order highstand sea level, and Albian second order sea level rise. The coeval climatic shift toward more humid conditions resulted in the clastic-dominated deposition of the organic-lean regressive units of SQ 2 (HST and LST of Alam El Bueib, Alamein, and Dahab formations) and SQ 3 (HST and LST of the lower–upper Kharita Formation) in marginal marine settings under anoxic–dysoxic to oxic conditions. The HST and LST deposits of the SQ 2 and SQ 3 show poor to good organic richness of early–mid mature (early–peak oil-window) oil/gas-prone and gas/oil-prone organic matter, respectively and exhibit average fair oil source rock potential with no gas generation.
... JG Field has been put on production since 2002; targeting the fluvial sands building the "Lower Safa" member of the Middle Jurassic Khatatba Formation (Strating and Postuma, 2008). Khatatba Formation has been divided, lithostratigraphyically, into six members namely, from below upwards; Lower Safa C, Lower Safa B, Lower Safa A, Kabrit, Upper Safa B, and Upper Safa A (Ahmed and Hassan, 2019). Despite some literature investigated NEAG area, particularly JG Field, (e.g. ...
Inadequate delineation of reservoir-heterogeneities, along with charge-timing confirmation, can considerably mislead exploration-development phases of petroleum. Therefore, precisely depicting the reservoir-architecture is crucial for avoiding exploration failures. To this end, integrated approach of various facies analysis and modeling-related disciplines; e.g. seismic facies, and GR-log motifs; was applied, in this study, to develop a depositional-model capable of aiding in stochastically-mapping reservoir heterogeneity and quality of the Jurassic estuarine depositional-system at JG-Field. To overcome the issue of sparse well control and scarcity of promising discoveries from deep-buried intervals in the study area, stochastic 3D-geocellular reservoir modeling, constrained by seismic attribute analysis, was performed to render a lateral prediction of different facies constituting the Jurassic succession. Predicting organic maturities and retrieving past geologic processes controlled sedimentary basin evolution were also a matter of importance to confirm hydrocarbon-charging to reservoir intervals. Accordingly, 1D-basin model was established so as to complete the story of petroleum system analysis in the area. We utilized dataset of seismic, log, core, and thin-section data; and applied both object-based and pixel-based, SIS (Sequential Indicator-Simulation) and SGS (Sequential Gaussian-Simulation), stochastic modeling algorithms upon simulating rock and fluid properties. The results show that the Jurassic succession constitutes a third-order depositional sequence of fluvio-estuarine units, subdivided into five sedimentary facies-associations. Fluvial and tidal-bar facies associations enrich medium-grained sandstones, deposited in subaerial and subaqueous conditions respectively, featuring significant reservoir quality. Given best reservoir-quality, and considerable thickness, the tidal sand-bars ought to catch attention of future development strategies and be considered for investigation in similar settings.
... The recent natural gas discoveries from the Khatatba Formation attracted the attention of many petroleum geologists to further investigate its hydrocarbon potential in the Abu Gharadig and Shushan basins (e.g. Shalaby et al., 2014;El Nady et al., 2016;Ahmed and Hassan, 2019;Lotfy et al., 2020). However, the hydrocarbon potential of the Khatatba Formation in the Matruh Basin is still under-explored. ...
... Abu Tunis-1X well) and in other deep southern basinal areas, e.g. NE Abu Gharadig Basin (Jd-4 well) in the north Western Desert (Guiraud et al., 2001;Gentzis et al., 2018;Ahmed and Hassan, 2019). ...
... During that time, the Khatatba Formation was deposited in relatively shallower shallow marine settings in the Shushan Basin (Shalaby et al., 2011(Shalaby et al., , 2012a(Shalaby et al., , 2014El Nady et al., 2016) and in relatively deeper shallow marine settings in the Abu Gharadig Basin (Ahmed and Hassan, 2019). As a result, the Khatatba Formation in the Abu Gharadig Basin shows a better kerogen quality (II-III) because of the dominance of the marine organic matter in contrast to that (III to III-II) of the Shushan Basin, where the terrestrial organic matter is more dominant. ...
The present national and international pursuit of converting Egypt into a regional hub of natural gas in the East Mediterranean region resulted in conducting extensive exploration activities in several areas of northern Egypt. Therefore, organic petrographic, geochemical, and geophysical analyses were carried out on the upper Khatatba Formation from the OBA 2-2 A well in the Matruh Basin.
Restoration of the original sedimentological and geochemical characteristics of the upper Khatatba Formation suggest deposition of this formation in deltaic settings. Few shale and partly calcareous shale units of the Upper Safa and the uppermost Zahra members accumulated in TST in prodelta settings under dysoxic-anoxic conditions. These shale units had an original gas/oil-prone organic facies BC. Other shales and partly calcareous shales of the Upper Safa and Zahra members accumulated in HST in deltafront settings under relatively oxic conditions and had an original lower gas-prone organic facies C.
The Upper Safa Member had an original active fair to excellent organic richness (0.76–7.35, avg. 3.38 TOCo(live) wt%) and hydrocarbon source rock potential (S2o: 2.22–17.97, avg. 8.05 mg HC/g org. C). It was characterised mainly by original active mixed gas/oil-prone kerogen type IIIo(live)-IIo(live) (HIo(live): 200.27–297.34, avg. 238.03 mg HC/g TOCo(live)) and subordinately by gas-prone kerogen type IIIo(live) (HIo(live): 181.50 mg HC/g TOCo(live)). The Upper Safa Member had original poor to fair proportions of active oil-prone (0.15–1.47, avg 0.68 TOCo(live, oil) wt%) and higher fair to very good proportions of active gas-prone (0.61–5.88, avg. 2.70 TOCo(live, gas) wt%) kerogens. The Upper Safa Member originally possessed poor to very good oil (S2o(oil): 0.44–3.59, avg. 1.16 mg HC/g org. C) and good to very good gas (S2o(gas): 1.77–14.37, avg. 6.44 mg HC/g rock) generation potential. The carbonates and partly calcareous shales of the uppermost Safa and the Zahra members possessed poor oil and gas generation potential due to their organic-lean status.
The present-day organic geochemical characterization indicates that the Upper Safa Member still shows active fair to excellent organic richness (0.68–6.75, avg. 3.11 TOCpd(live) wt%). However, this member shows a relatively lower present-day good to very good/excellent source rock potential (S2pd: 1.33–10.78, avg. 4.83 mg HC/g rock) and lower active kerogen quality IIIpd(live) (HIpd(live): 115.97–198.21, avg. 151.07 mg HC/g TOCpd(live)). This is related to the current high thermal maturation (gas-window: Tmax: 459–468, avg. 469 °C, thermal alteration index: TAI of 4-) and conversion of the original kerogen IIIo(live)-IIo(live) into oil and gas. The present-day high organic richness, high remaining generative potential, high shale volume of the thermally mature gas-prone kerogen, classify the Upper Safa Member as an active fair to excellent shale gas play in the Matruh Basin. Intrabasinal and interbasinal correlations across northwestern Egypt indicate that the upper Khatatba Formation shows locally and regionally dual source and reservoir rock characteristics due to the lateral facies changes.
... T max is the temperature at which the S 2 attains its maximum hydrocarbon generation. 31 It accounts for the hydrogen and oxygen richness of the shale. On the other hand, TOC is an important indicator of organic richness in shale plays. ...
Prediction of thermal maturity index parameters in organic shales plays a critical role in defining the hydrocarbon prospect and proper economic evaluation of the field. Hydrocarbon potential in shales is evaluated using the percentage of organic indices such as total organic carbon (TOC), thermal maturity temperature, source potentials, and hydrogen and oxygen indices. Direct measurement of these parameters in the laboratory is the most accurate way to obtain a representative value, but, at the same time, it is very expensive. In the absence of such facilities, other approaches such as analytical solutions and empirical correlations are used to estimate the organic indices in shale. The objective of this study is to develop data-driven machine learning-based models to predict continuous profiles of geochemical logs of organic shale formation. The machine learning models are trained using the petrophysical wireline logs as input and the corresponding laboratory-measured core data as a target for Barnett shale formations. More than 400 log data and the corresponding core data were collected for this purpose. The petrophysical wireline logs are γ-ray, bulk density, neutron porosity, sonic transient time, spontaneous potential, and shallow resistivity logs. The corresponding core data includes the experimental results from the Rock-Eval pyrolysis and Leco TOC measurements. A backpropagation artificial neural network coupled with a particle swarm optimization algorithm was used in this work. In addition to the development of optimized PSO-ANN models, explicit empirical correlations are also extracted from the fine-tuned weights and biases of the optimized models. The proposed models work with a higher accuracy within the range of the data set on which the models are trained. The proposed models can give real-time quantification of the organic matter maturity that can be linked with the real-time drilling operations and help identify the hotspots of mature organic matter in the drilled section.
... The indirect approaches require an appropriate sample to log calibration in order to accurately predict TOC values for source rock assessment (Ahmed and Hassan, 2019). One of the key factors considered to describe and assess the unconventional resources is TOC. ...
Sembar Formation of Cretaceous encountered in Khajari-01 and Miran-01 wells, which are located in the Southern Indus Basin (SIB), Pakistan. Total organic carbon (TOC) content is generally measured by traditional methods such as the evaluation of side wall cores and formation cuttings in a geochemical lab. Data obtained from these experimental techniques are not continuous and also a time-consuming process. A solution to this problem is high resolution and continuous information obtained from well logs. Different methods were used to estimate TOC through well logs. Among those methods, four methods have been chosen to estimate TOC in the current research, i.e., Density Log, Spectral Gamma-Ray Log, ΔlogR, and Multivariate Fitting methods. The TOC estimated values have been correlated with well cuttings TOC values to optimize a method for TOC estimation through well logs. Fourteen well cutting samples of Sembar Formation from Khajari-01 well and seven samples from Miran-01 well have been selected for measurements of geochemical parameters. These parameters were used for source rock evaluation of the formation to determine the quality, quantity, and maturity of the Sembar Formation. Modified van-Krevlen diagram of Hydrogen Index (HI) versus Oxygen Index (OI) and Langford diagram of S2 versus TOC indicates that Sembar Formation in Khajari-01 well contain kerogen type-III (gas prone) compare to Miran-01 well that contains kerogen type-IV which makes it non-productive. The organic richness results indicate that TOC in Khajari-01 well is poor to very good while in Miran-01 a fair to good generation potential exist. Maturity indicators i.e., Pyrolysis Temperature (Tmax) and Production Index (PI) values show an immature to early mature zone for Khajari-01 well and over-mature zone in Miran-01 within the Sembar Formation. Density Log, Spectral Gamma-Ray Log, and Multivariate Fitting methods have poor coefficient of determination (R²) values between the estimated TOC (from well logs) with well cuttings tested samples TOC values. It has been inferred from data obtained using ΔlogR method that it has good R² value between well logs estimated TOC and actual laboratory measured TOC in both wells which is optimized for future study in Southern Indus Basin, Pakistan.
Airborne spectral gamma-ray survey data were processed using Th-normalization technique for oil and gas exploration in the Qaret El-Soda area, Western Desert of Egypt. This technique was applied to suppress the effects of surface lithology, which are the main factors influencing the variation of radioelement content in rocks. Normalization of K and U by thorium yielded residual potassium and residual uranium estimates. Possible occurrences of new hydrocarbon microseepages were determined by mapping low values of residual potassium and high values of residual uranium relative to potassium, which are indicated as DRAD values, which were obtained by subtracting residual potassium from residual uranium values (eUresid – Kresid). Lower residual values of K, which were associated with higher DRAD anomaly values, highlight areas of prospective hydrocarbon accumulations. The obtained results from quantitative analysis and interpretation of aeromagnetic data show sufficiently thick sediments, probably suitable for the accumulation of hydrocarbons. This means that the study area may possess a potential for hydrocarbon exploration if supported by other detailed geophysical and geochemical exploration techniques.
The Abu El Gharadiq Basin (AGB) is one of the largest Cretaceous rift basins in the northern district of the Western Desert of Egypt. The AGB underwent tectonic inversion in the Upper Cretaceous through horizontal shortening in the NW-SE direction. Detailed interpretation of seismic sections across discrete regions of this basin shows that the rocks deformed in two different depth-related deformation styles, which are partitioned across the base of the so called Bahariya Formation of Cenomanian age. The deeper, pre-Cenomanian rock units show contractional deformation forming tight folds and related fabrics while shallower, post-Cenomanian rock units display features of extensional deformation. These are essentially shallowly undulating open folds, associated with conjugate normal faults and tensional fractures. The deeper pre-Cenomanian tight anticlines pierce the upper rock units as diapiric-like intrusions that are seen on the seismic sections as hazy regions. We infer that the two different deformation styles above and below the Cenomanian rocks occurred simultaneously. The hazy regions on the seismic sections may result from lateral flow of shale rocks that give rise to chaotic structures near the anticlines. Mechanical anisotropy across the Cennomanian rock unit is inferred to be the main cause of simultaneous emergence of contractional and extensional deformations. Re-evaluation of fracture patterns of the northern rift basins in the Western Desert implies that the AGB originated in an extensional stepover region of a discrete, ENE-WSE trending, shear zone whose margins underwent inversions, developing two parallel thrust-dominated ridges, namely the crustal scale Kattaniya and Qattara-Alamein ridges.
