Application of watershed segmentation algorithm and supervised Bayesian classification in the evaluation of petrophysical parameters, pore properties, and lithofacies using 3D seismic data, wireline logs, and SEM images: A case study from Abadan Plain, SW Iran DOI Creative Commons
Hamed Ghanbarnejad Moghanloo, Mohammad Ali Riahi

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 7, 2023

Abstract In this paper, an integrated workflow based on recent geoscience data is presented for assessing the reservoir characterization and structural interpretation of Burgan formation, a highly productive formation in Abadan plain, SW Iran. Utilizing newly acquired high-resolution SEM images, we evaluated pore size, distribution, aspect ratio formation. The watershed segmentation algorithm also capable detecting throats closed pores. porosity fractions from images are used calibration log at several well locations order to perform petrophysical modeling. Since facies behavior complex study area, utilized supervised Bayesian classifier using P-wave velocity, density, dataset. confusing matrix machine learning metrics including Accuracy (97.01%), Precision (93.88%), F1 Score (94.16%), False Positive Rate (2.52%), indicate that has been properly trained locations. A reasonable match evident between modeled parameters true (core) water saturation location test well. Furthermore, have demonstrated validity assumptions concerning dominance extensional structure plain by interpreted seismic data. can be optimize drilling operations reduce risks similar geological settings studied

Language: Английский

Advanced AI approach for enhanced predictive modeling in reservoir characterization within complex geological environments DOI
Wakeel Hussain, Muhammad Ali,

Rakhshanda Sadaf

et al.

Modeling Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 10(4), P. 5043 - 5061

Published: June 14, 2024

Language: Английский

Citations

11
Prospect Evaluation of the Cretaceous Yageliemu Clastic Reservoir Based on Geophysical Log Data: A Case Study from the Yakela Gas Condensate Field, Tarim Basin, China DOI Creative Commons
Wakeel Hussain, Muhsan Ehsan, Lin Pan

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(6), P. 2721 - 2721

Published: March 14, 2023

This paper evaluated the oil and gas potential of Cretaceous Yageliemu clastic reservoir within Yakela condensed field lying in Kuqa Depression, Tarim Basin, China. The petrophysical properties interest zones area were characterized using geophysical logs from five wells. results reveal that gas-bearing are by high resistivity, good permeability (K) effective porosity (Φeff), low water saturation (Sw), shale concentration (Vsh), reflecting clean sand. distribution model showed these shales have no major influence on fluid saturation. average volume, porosity, hydrocarbon indicate Formation studied contains prospective properties. spatial parameters, rock typing (RRT), lithofacies analyzed cross plots litho (volumetric analysis), iso-parametric representations characteristics, cluster analysis, self-organizing feature maps, respectively. southeastern northeastern regions research should be ignored because their concentrations. sediments southwest northwest include most intervals considered for future exploration development fields study area.

Language: Английский

Citations

21
Assessing the hydrocarbon potential of the Kadanwari gas field using integrated seismic and petrophysical data DOI Creative Commons
Zahid Khan,

Zulfiqar Ahmed,

Muhammad Tayyab Naseer

et al.

Journal of Petroleum Exploration and Production Technology, Journal Year: 2024, Volume and Issue: 14(6), P. 1349 - 1364

Published: March 28, 2024

Abstract Kadanwari is a major gas-producing field in Pakistan's Lower Indus Basin (LIB), extensively explored for optimized production. However, the reservoir sands of Goru Formation (LGF), deposited complex river-dominated delta, bear severe variability and hinder accurate facies approximation optimal Furthermore, regionally extended NNW-SSE directed horst graben structures significantly compartmentalized these facies. The main E-sand interval analyzed its geological properties, depositional environment, distribution. integration various approaches, including seismic interpretation, attribute extraction, well-based modeling, petrophysical evaluation, proved significant evaluating heterogeneous tectonically influenced E-sands. discontinuity substantially highlighted structural style aided analyzing geometries faults. low values frequency (< 10 Hz) signified entrapped gas-bearing along faulted zones. high responses instantaneous amplitude sweetness profoundly illuminated gas-significant deposits throughout association with well-identified gas-prone sand outcomes neutron-density crossplot depicted having density 2.3 g/cc) good porosity (12%) assessment cements. modeling distinguished between clean intermixed sand-shale Petrophysical analysis revealed net pay 14 m within gas saturation about 68%. adopted approach robust efficient, employing limited data set developing well-associated potential zone delineation arrangements. techniques can be optimistic LGF's demarcation Basin.

Language: Английский

Citations

7
Predictive Modeling of soil salinity integrating remote sensing and soil variables: An ensembled deep learning approach DOI Creative Commons
Sana Arshad, Syed Jamil Hasan Kazmi, Endre Harsányi

et al.

Energy Nexus, Journal Year: 2025, Volume and Issue: unknown, P. 100374 - 100374

Published: Feb. 1, 2025

Language: Английский

Citations

0
Evaluating the Ranikot formation in the middle Indus Basin, Pakistan as a promising secondary reservoir for development DOI Creative Commons
Muhsan Ehsan, Rujun Chen, Muhammad Ali

et al.

Geomechanics and Geophysics for Geo-Energy and Geo-Resources, Journal Year: 2025, Volume and Issue: 11(1)

Published: March 24, 2025

Language: Английский

Citations

0
Pore pressure prediction based on conventional well logs and seismic data using an advanced machine learning approach DOI Creative Commons
Muhsan Ehsan, Umar Manzoor, Rujun Chen

et al.

Journal of Rock Mechanics and Geotechnical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Citations

3
A Comparative Study Based on Petrophysical and Cluster Analysis Approach for Identification of Rock Types in Heterogeneous Sandstone Reservoirs DOI Creative Commons

Muhammad Nofal Munir,

Mohammad Zafar,

Abid Ali

et al.

ACS Omega, Journal Year: 2024, Volume and Issue: 9(31), P. 33397 - 33407

Published: July 25, 2024

To delineate a powerful reservoir model, rock type identification is an essential task. Recognizing intervals with promising quality in heterogeneous reservoir, such as the Pab Formation, using well logs critical for better exploration, because coring programs are always impractical due to time and cost constraints. Rock types described by specific log responses, which ultimately distinguished help of electrofacies. The current study uses cluster analysis technique evaluation identified sand units. K-means employed define electrofacies, classified into four on basis quality, from bad excellent. typing has been done wells, correlation made depict changes From well-to-well correlation, it can be inferred that Formation at lower portion Zamzama-02 05 wells excellent defined 4. Zamzama-03 southwestern region, other hand, good moderate demonstrated dominating 3 2, respectively. applied prediction studied field provides continuous entire reservoir. Using this methodology defining cost-effective, requires less demarcation zones interest, more accurate than manual thick Formation. approach not only useful exploitation but also sandstone reservoirs elsewhere.

Language: Английский

Citations

2
An integrated study for seismic structural interpretation and reservoir estimation of Sawan gas field, Lower Indus Basin, Pakistan DOI Creative Commons
Muhsan Ehsan,

Muhammad Arslan Shakeel Toor,

Muhammad Iqbal Hajana

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(5), P. e15621 - e15621

Published: April 20, 2023

The information about the subsurface structure, type of fluids present in reservoir, and physical properties rocks is essential for identifying potential leads. integrated approach petrophysical analysis, seismic data interpretation, attributes lithology, mineralogy identification, Gassmann fluid substitution were used this purpose. structural interpretation with help indicated extensional regime horst graben structures study area. two negative flower are cutting entire Cretaceous deposits. depth contour map also indicate favorable hydrocarbon accumulation. four possible reservoir zones Sawan-01 well Judge-01 at B sand C levels identified based on interpretation. main lithology Lower Goru Formation sandstone thin beds shale. clay types confirm marine depositional environment Formation. water increased P-wave velocity density. affected shear wave varies slightly due to density changes. cross plots P-impedance versus Vp/Vs ratio differentiate low from shaly high values S-impedance plot increasing gas saturation a decrease impedance values. Lambda-Rho Mu-Rho plot.

Language: Английский

Citations

4
A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China DOI Creative Commons
Zongbin Liu,

Jianmin Zhu,

Bo Tian

et al.

Frontiers in Earth Science, Journal Year: 2024, Volume and Issue: 12

Published: Dec. 16, 2024

As the demands for hydrocarbon exploration continue to rise, identification of thin sand bodies becomes significantly important subsequent petroleum and development efforts. However, traditional inversion techniques struggle with complex subsurface structures because low frequency seismic data. To characterize architecture reservoir precisely, a novel method is applied improve resolution data high interpretation accuracy. In this study, we take X Oilfield in Eastern China as an example, adopted approach combining spectral decomposition convolutional neural networks (CNNs) within genetic algorithm (GA) framework inversion. The CNNs are adept at recognizing interpreting spatial configurations data, thereby establishing correlation between attributes body distributions. GA helps get optimal solution fast speed. results reveal that model's thickness predictions closely match actual measurements wells, new horizontal well's alignment predicted output reaching accuracy 85.1%. Compared methods, our requires less This may find wider application, especially offshore oilfields few wells quality

Language: Английский

Citations

1
Integrating watershed segmentation algorithm and supervised Bayesian classification for the assessment of petrophysical parameters, pore properties, and lithofacies: a case study from Abadan Plain, SW Iran DOI
Hamed Ghanbarnejad Moghanloo, Mohammad Ali Riahi

Earth Science Informatics, Journal Year: 2023, Volume and Issue: 16(4), P. 3913 - 3930

Published: Oct. 31, 2023

Language: Английский

Citations

3