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Collaborating Authors
Berkine Basin (Trias/Ghadames Basin)
In this study, we interpreted a cumulative 600m acoustic image log across the Triassic to Cambro-Ordovician interval in the Berkaoui oil field, Algeria. We interpreted 40 distinct breakout zones which have a combined length of 210m. These breakouts are aligned in the NNE-SSW direction indicating a mean maximum horizontal stress (SHmax) azimuth of 110°N. The observed breakouts are ranked as A-Quality following the World Stress Map ranking guidelines. The angular width of each breakout has been inferred from the image log analysis and the same has been utilized to infer the SHmax gradient by stress polygon approach following the frictional faulting mechanism. The stress polygon across all the breakout intervals provides a practical Shmax range between 24.7-31.1 MPa/km, with an average gradient of ~ 27 MPa/km. Considering the Shmin range across the studied intervals, we infer a SHmax/Shmin ratio dominantly between 1.40-1.65, which is a much narrower and better-constrained range when compared to the previously published ranges from nearby fields with the same stratigraphy. The relative magnitudes of the in-situ stresses indicate a strike-slip faulting regime in the Berkaoui field. This study presents the utility of image log analysis and integration of breakout interpretation to obtain a more robust geomechanical model with reduced SHmax uncertainty.
- North America > United States (1.00)
- Asia (1.00)
- Africa > Middle East > Algeria > Illizi Province (0.28)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud (0.28)
- Phanerozoic > Paleozoic > Ordovician (1.00)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.46)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.75)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.47)
- Geology > Structural Geology > Tectonics > Plate Tectonics (0.46)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.72)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Zubair Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Mishrif Formation (0.99)
- Africa > Middle East > Egypt > Western Desert > Greater Western Dester Basin > Abu Gharadig Basin > Abu Gharadig Field (0.99)
- (10 more...)
CONSTRAINING MAXIMUM HORIZONTAL STRESS USING WELLBORE BREAKOUTS -- A CASE STUDY FROM ORDOVICIAN TIGHT RESERVOIR OF NORTHEASTERN OUED MYA BASIN, ALGERIA
Baouche, Rafik (University MHamed Bougara Boumerdes) | Sen, Souvik (Baker Hughes) | Ganguli, Shib Sankar (CSIR-National Geophysical Research Institute) | Benmamar, Salim (Baker Hughes) | Kumar, Prakash (CSIR-National Geophysical Research Institute)
In this study, we interpret the maximum horizontal stress (SHmax) azimuth from the breakout positions of wellbore and attempt to constrain the SHmax gradient based on the interpreted breakout width. A cumulative of 110 m of breakouts were deciphered within the Ordovician Hamra Quartzite interval of the Oued Mya Basin from a 138 m of acoustic image log. These breakouts were ranked as A-Quality following the World Stress Map ranking guidelines. We infer a mean SHmax orientation of N28E 8. Following the frictional faulting mechanism and stress polygon approach, measurement of minimum horizontal stress (Shmin) from minifrac tests and observations of compressive failures from acoustic image log provided strong constraints on the SHmax magnitude in the reservoir interval in the absence of core-measured rock strength. Interpreted breakout widths exhibit a range between 32.6 and 90.81, which indicated a SHmax range of 24.434.7MPa/km. The average breakout width of 62.58 translates to a narrower SHmax gradient range, varying between 27.2 and 31.2 MPa/km. The relative magnitudes of the principal stresses indicate a strong strike-slip tectonic stress state. Considering all the uncertainties, we infer a SHmax/Shmin ratio of 1.411.81 within the Ordovician interval.
- Africa > Middle East > Algeria > Eastern Algeria (0.71)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud (0.28)
- Phanerozoic > Paleozoic > Ordovician (0.92)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.46)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.53)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.34)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.70)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Zubair Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Mishrif Formation (0.99)
- Africa > Middle East > Tunisia > Kebili Governorate > Chotts Basin > Hamra Quartzite Formation (0.99)
- (11 more...)
A class-rebalancing self-training semisupervised learning for imbalanced data lithology identification
Yin, Shitao (Chinese Academy of Geological Sciences, China University of Geosciences (Beijing)) | Lin, Xiaochun (National Research Center for Geoanalysis) | Zhang, Zhifeng (China University of Geosciences (Beijing)) | Li, Xiang (China University of Geosciences (Beijing))
ABSTRACT Lithologic identification plays a crucial role in petroleum geologic exploration, and machine learning (ML) has become increasingly prevalent in intelligent lithology identification in recent years. However, identifying lithologies presents challenges due to a lack of lithologic labels and an imbalanced distribution of lithologies. To address this issue and obtain satisfactory lithologic identification results, this study investigates a class-rebalancing self-training (CReST) lithology identification framework. This framework uses logging data and limited lithologic labels as input and achieves promising lithology classification through the CReST approach. Four ML algorithms with high overall performance are selected from 25 common algorithms to establish CReST models, such as bagging classifier, extra trees classifier, random forest classifier, and support vector classifier. The classification results of the models are compared and analyzed under three conditions. The experimental findings indicate that (1) under label scarcity, the effect of category recognition varies greatly with different sample numbers; (2) under self-training (ST), overall performance is improved, but the difference in performance caused by category imbalance also increases; and (3) under CReST framework, the model effectively resolves the identification problems caused by a lack of labels and an imbalanced category distribution. Specifically, the precision of identifying categories with fewer samples is improved by more than 20%.
- Asia > China > Heilongjiang Province (0.28)
- Africa > Middle East > Algeria (0.28)
- Asia > China > Qinghai > Qaidam Basin (0.99)
- Asia > China > Northeast China > Songliao Basin > Yingcheng Formation (0.99)
- Asia > China > Jilin > Yanji Basin > Jilin Field (0.99)
- (4 more...)
Reconstruction of Missing Well-Logs Using Facies-Informed Discrete Wavelet Transform and Time Series Regression
Ren, Quan (School of Earth Sciences and Engineering, Hohai University) | Zhang, Hongbing (CERENA/DER, Universidade de Lisboa, Instituto Superior Técnico) | Azevedo, Leonardo (School of Earth Sciences and Engineering, Hohai University (Corresponding author)) | Yu, Xiang (CERENA/DER, Universidade de Lisboa, Instituto Superior Técnico) | Zhang, Dailu (Design & Consulting Corp, Nanjing Hydraulic Research Institute) | Zhao, Xiang (School of Earth Sciences and Engineering, Hohai University) | Zhu, Xinyi (School of Earth Sciences and Engineering, Hohai University) | Hu, Xun (School of Earth Sciences and Engineering, Hohai University)
Summary Geophysical logging is widely used in lithofacies identification, reservoir parameter prediction, and geological modeling. However, it is common to have well-log sections with low-quality and/or missing segments. Repeating the well-log measurements is not only expensive but might also be impossible depending on the condition of the borehole walls. In these situations, reliable and accurate well-log prediction is, therefore, necessary in different stages of the geomodeling workflow. In this study, we propose a time series regression model to predict missing well-log data, incorporating facies information as an additional geological input and using discrete wavelet transform (DWT) to denoise the input data set. The main contributions of this work are threefold: (i) We jointly use facies information with well logs as the input data set; (ii) we use DWT to denoise the input data and consequently improve the signal-to-noise ratio of the input data; and (iii) we regard the depth domain as the time domain and use a time series regression algorithm for log reconstruction modeling. We show a real application example in two distinct scenarios. In the first, we predict missing well-log intervals. In the second, we predict complete well logs. The experimental results show the ability of the proposed prediction model to recover missing well-log data with high accuracy levels.
- Asia > China (0.94)
- Africa > Middle East > Algeria (0.46)
- Asia > China > South China Sea > Zhujiangkou Basin (0.99)
- Asia > China > Sichuan > Sichuan Basin (0.99)
- Asia > China > Heilongjiang > Songliao Basin > Daqing Field > Yian Formation (0.99)
- (3 more...)
Novel Structural Aspects of Heavy-Crude-Derived Asphaltene Molecules for Investigating the Crude Mix Processability in Refinery Operation
Das, Raj K. (Corporate R&D Centre, Bharat Petroleum Corporation Ltd.) | Voolapalli, Ravi K. (Corporate R&D Centre, Bharat Petroleum Corporation Ltd.) | Upadhyayula, Sreedevi (Department of Chemical Engineering, Indian Institute of Technology-Delhi (Corresponding author)) | Kumar, Rajeev (Corporate R&D Centre, Bharat Petroleum Corporation Ltd. (Corresponding author))
Summary In this paper, we investigate the role of asphaltenes derived from heavy crudes, which dictates the behavior of crude mix properties for hassle-free downstream refinery operation. Combined characterization techniques such as proton nuclear magnetic resonance (H-NMR), cross-polarization magic-angle-spinning carbon-13 (CP/MAS C)-NMR, heteronuclear single-quantum coherence (HSQC), Fourier transform infrared (FTIR), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) are used for the detailted study of Ratwai and Ras Gharib (RG)-derived asphaltenes to validate their structural role in selecting the optimal crude mix. As per our investigation, when the polyaromatic core of asphaltene structures are less substituted, the availability of aromatic hydrogen is more; it exhibits a stable crude mix as compared to heavy crudes that have more aromatic core substitution, despite the crudes possessing similar asphaltene content and physicochemical properties. This finding is further extended to West Canadian (WC) and Belayim (BL) heavy crudes for operational suitability. In this study, the key feature is to develop a CP/MAS C-NMR-based robust and quick characterization technique that could potentially become a prescreening method to assess crude oil compatibility and its various blend processability in the refinery system. Other characterization techniques, such as H-NMR, HSQC, FTIR, TGA, and XRD, would corroborate and confirm the reliability of the data obtained by CP/MAS C-NMR.
- North America > United States (0.95)
- Africa > Middle East > Algeria (0.28)
- Energy > Oil & Gas > Upstream (1.00)
- Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.75)
- North America > Canada > Alberta > Athabasca Oil Sands > Western Canada Sedimentary Basin > Alberta Basin (0.99)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud > Oued Mya Basin > Hassi Messaoud Field (0.99)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud > Berkine Basin (Trias/Ghadames Basin) > Hassi Messaoud Field (0.99)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene (1.00)
- Facilities Design, Construction and Operation > Flow Assurance > Precipitates (paraffin, asphaltenes, etc.) (1.00)
A class-rebalancing self-training semisupervised learning for imbalanced data lithology identification
Yin, Shitao (Chinese Academy of Geological Sciences, China University of Geosciences (Beijing)) | Lin, Xiaochun (National Research Center for Geoanalysis) | Zhang, Zhifeng (China University of Geosciences (Beijing)) | Li, Xiang (China University of Geosciences (Beijing))
ABSTRACT Lithologic identification plays a crucial role in petroleum geologic exploration, and machine learning (ML) has become increasingly prevalent in intelligent lithology identification in recent years. However, identifying lithologies presents challenges due to a lack of lithologic labels and an imbalanced distribution of lithologies. To address this issue and obtain satisfactory lithologic identification results, this study investigates a class-rebalancing self-training (CReST) lithology identification framework. This framework uses logging data and limited lithologic labels as input and achieves promising lithology classification through the CReST approach. Four ML algorithms with high overall performance are selected from 25 common algorithms to establish CReST models, such as bagging classifier, extra trees classifier, random forest classifier, and support vector classifier. The classification results of the models are compared and analyzed under three conditions. The experimental findings indicate that (1) under label scarcity, the effect of category recognition varies greatly with different sample numbers; (2) under self-training (ST), overall performance is improved, but the difference in performance caused by category imbalance also increases; and (3) under CReST framework, the model effectively resolves the identification problems caused by a lack of labels and an imbalanced category distribution. Specifically, the precision of identifying categories with fewer samples is improved by more than 20%.
- Asia > China > Heilongjiang Province (0.28)
- Africa > Middle East > Algeria (0.28)
- Asia > China > Qinghai > Qaidam Basin (0.99)
- Asia > China > Northeast China > Songliao Basin > Yingcheng Formation (0.99)
- Asia > China > Jilin > Yanji Basin > Jilin Field (0.99)
- (4 more...)
Missing well-log reconstruction using a sequence self-attention deep-learning framework
Lin, Lei (China University of Geosciences) | Wei, Hao (China University of Geosciences) | Wu, Tiantian (China University of Geosciences) | Zhang, Pengyun (China Oilfield Services Limited) | Zhong, Zhi (China University of Geosciences) | Li, Chenglong (China University of Geosciences)
ABSTRACT Well logging is a critical tool for reservoir evaluation and fluid identification. However, due to borehole conditions, instrument failure, economic constraints, etc., some types of well logs are occasionally missing or unreliable. Existing logging curve reconstruction methods based on empirical formulas and fully connected deep neural networks (FCDNN) can only consider point-to-point mapping relationships. Recurrently structured neural networks can consider a multipoint correlation, but it is difficult to compute in parallel. To take into account the correlation between log sequences and achieve computational parallelism, we develop a novel deep-learning framework for missing well-log reconstruction based on state-of-the-art transformer architecture. The missing well-log transformer (MWLT) uses a self-attention mechanism instead of a circular recursive structure to model the global dependencies of the inputs and outputs. To use different usage requirements, we design the MWLT in three scales: small, base, and large, by adjusting the parameters in the network. A total of 8609 samples from 209 wells in the Sichuan Basin, China, are used for training and validation, and two additional blind wells are used for testing. The data augmentation strategy with random starting points is implemented to increase the robustness of the model. The results show that our proposed MWLT achieves a significant improvement in accuracy over the conventional Gardner’s equation and data-driven approaches such as FCDNN and bidirectional long short-term memory, on the validation data set and blind test wells. The MWLT-large and MWLT-base have lower prediction errors than MWLT-small but require more training time. Two wells in the Songliao Basin, China, are used to evaluate the cross-regional generalized performance of our method. The generalizability test results demonstrate that density logs reconstructed by MWLT remain the best match to the observed data compared with other methods. The parallelizable MWLT automatically learns the global dependence of the parameters of the subsurface reservoir, enabling an efficient missing well-log reconstruction performance.
- Asia > China (1.00)
- North America > United States > Colorado > Garfield County (0.28)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
Integration of 1-D Geomechanical Model for Minimum Horizontal Stress Estimation and Validation with Micro-frac Tests – Case Study from Touggourt Field, Algeria
Podder, Tuhin (Baker Hughes) | Chakrabarti, Prajit (Baker Hughes) | Sen, Souvik (Baker Hughes) | Ouriri, Feriel (Sonatrach) | Aichour, Imad (Sonatrach) | Hammoudi, Abdelmalek (Sonatrach) | Bouarfetine, Djilali (Sonatrach) | Perumalla, Satya (Baker Hughes)
Abstract This study presents comprehensive geomechanical modeling of the tight Triassic reservoirs from the Touggourt field, eastern Algeria. The primary objective was to constrain minimum horizontal stress in the T1 and T2 reservoirs by microfrac testing. Wireline logs, direct pore pressure measurements, acoustic and resistivity image logs were integrated for geomechanical modeling. A strike-slip tectonic stress regime with NW-SE SHmax orientation was inferred. A pre-job geomechanical model was prepared for selecting optimum intervals for microfrac testing. Contrast in horizontal stress magnitudes, density-porosity, and rock-mechanical properties, expected breakdown pressure being within tool limit, and in-gauge caliper response have been considered for choosing the microfrac test intervals, while honoring the operator’s geological objectives. Based on the microfrac test data, we inferred a 0.88-0.94 psi/ft Shmin gradient with 1.04-1.08 psi/ft breakdown pressure gradient within these Triassic reservoirs. Integrated geomechanical approach in the pre-planning as well as real-time advisory facilitated successful formation break down in a very tight and strong lithofacies. High quality data acquired during microfrac operation yielded confident fracture closure interpretation and post-job geomechanical model calibration, which has critical implications in future drilling and completion optimization.
- Phanerozoic > Mesozoic > Triassic (0.61)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.47)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.47)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.35)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Zubair Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Mishrif Formation (0.99)
- Africa > Middle East > Egypt > Western Desert > Greater Western Dester Basin > Abu Gharadig Basin > Abu Gharadig Field (0.99)
- (11 more...)
Fractures Characterization and Their Impact on the Development of a Tight Oil Field
Conde, Oliver Rojas (Texas A&M University, College Station) | Silva, Henry Galvis (Texas A&M University, College Station) | Doghmane, Mohamed Zinelabidine (University of Sciences and Technology, Bab Ezzouar, Algiers)
Abstract Revived interest in the Hassi Toumiet area has been sparked by oil discoveries in the Ordovician Formation near Hassi Messaoud field. However, the Hamra Quartzite reservoir in Hassi Toumiet has thinned and has poor quality compared to the Hassi Guettar field. Several studies have been conducted further research in Hassi Toumiet, located north of the Amguid-El-Biod axis, through 3D seismic and wells, resulting in new discoveries. Understanding the natural fractures in the area is crucial for its development, so a study was done using core samples, borehole imagery, and 3D seismic data. The study found three fault networks, with the dominant orientation being ENE-WSW and secondary orientation being NW-SE. Analysis of well cores showed low density of mostly cemented fractures, confirmed by borehole imagery. The fractures were found to be sparse, poorly connected, and strongly cemented, but this should be taken into consideration with respect to the well's verticality.
- North America > United States (1.00)
- Europe (0.94)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud (0.57)
- Geology > Rock Type (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Structural Geology (0.96)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Faults and fracture characterization (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Characterization of Maximum Horizontal Stress from Wellbore Failures – A Case Study from the Tight Paleozoic Hamra Quartzite Oil Reservoir of Oued Mya Basin, Algeria
Baouche, Rafik (University M’Hamed Bougara Boumerdes) | Sen, Souvik (Baker Hughes) | Benmamar, Salim (Baker Hughes) | Perumalla, Satya (Baker Hughes)
Abstract The Cambro-Ordovician Hamra Quartzite Formation is one of the important reservoirs from Algerian Sahara. The objectives of this study were to characterize the wellbore breakouts and constrain the maximum horizontal stress (Shmax) based on the inferred compressive failures within the Paleozoic reservoir. A-Quality breakouts were deciphered within the reservoir interval from a cumulative of 138m of acoustic image log indicating a mean SHmax orientation of N118˚E±8˚. Interpreted breakout widths exhibit a range between 32.6˚ and 90.81˚, which indicated a SHmax range of 24.4-34.7 MPa/km. The average breakout width of 62.58˚ translates to a SHmax gradient range of 27.2 and 31.2 MPa/km. The relative magnitudes of the principal stresses indicate a strong strike-slip tectonic stress state with a SHmax/Shmin ratio of 1.41-1.81 within the Ordovician interval. Following the frictional faulting-based stress polygon approach, measurement of minimum horizontal stress (Shmin) from minifrac tests and observations of compressive failures from acoustic image log provided strong constraints on the SHmax magnitude in the studied Ordovician tight reservoir interval in the absence of core-measured rock strength.
- Africa > Middle East > Algeria > Eastern Algeria (0.53)
- Africa > Middle East > Algeria > Ouargla Province > Hassi Messaoud (0.29)
- Phanerozoic > Paleozoic > Ordovician (1.00)
- Phanerozoic > Paleozoic > Cambrian (0.67)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.47)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Metamorphic Rock > Quartzite (0.65)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.51)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Zubair Formation (0.99)
- Asia > Middle East > Iraq > Basra Governorate > Arabian Basin > Widyan Basin > Mesopotamian Basin > Zubair Field > Mishrif Formation (0.99)
- Africa > Middle East > Tunisia > Kebili Governorate > Chotts Basin > Hamra Quartzite Formation (0.99)
- (11 more...)