Pub Date : 2021-09-01DOI: 10.1190/SEGAM2021-3595009.1
K. A. Khan
{"title":"Regional 3D velocity model building: An Upper Indus Basin case study","authors":"K. A. Khan","doi":"10.1190/SEGAM2021-3595009.1","DOIUrl":"https://doi.org/10.1190/SEGAM2021-3595009.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130952931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1190/SEGAM2021-3583194.1
Jorge Nustes Andrade, M. Baan
{"title":"Real-time prediction of the microseismic cloud size: A comparison between a physics-based model and a machine learning approach","authors":"Jorge Nustes Andrade, M. Baan","doi":"10.1190/SEGAM2021-3583194.1","DOIUrl":"https://doi.org/10.1190/SEGAM2021-3583194.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130218764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1190/SEGAM2021-3582926.1
S. Nasser, F. Morgan
{"title":"Joint inversion for an improved reservoir modeling and an accurate history matching","authors":"S. Nasser, F. Morgan","doi":"10.1190/SEGAM2021-3582926.1","DOIUrl":"https://doi.org/10.1190/SEGAM2021-3582926.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129833777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Submarine landslides (slides) are some of the most voluminous sediment gravity-flows on Earth and they dominate the stratigraphic record of many subaqueous basins. The general kinematics and internal structure of slides are relatively well-understood, although the way in which they increase in volume and internally deformed as they evolve, and how these processes relate to the development of their basal (shear) surface, remains largely unknown. We here use three high-resolution 3D seismic surveys (two broadband time-migrated seismic reflection datasets and a depth-migrated volume) from the Angoche Basin, offshore Mozambique to undertake detailed mapping and intra-slide strain analysis of a shallowly buried, large, and thus well-imaged submarine landslide (c. 530 km3). We also provide detailed documentation of the along-strike variations in the structural style and evolution of the toe region, and how these relate to the overall emplacement of the slide. Seismic attribute analysis image several key kinematic indicators, including broadly NW-trending (i.e., flow-parallel) lateral margins, longitudinal shears, and sub-orthogonal shears in the main body of the deposit, and broadly NE-trending (i.e., flow-normal) symmetric pop-up blocks in the toe region. The slide exhibits varying degrees of frontal emergence along strike, displaying a single frontal (toe) wall in the SW to a more complex, stair-step geometry in the NE. Basal grooves are noticeably absent, with a key observation being that contractional structures are locally observed c. 7 km downdip of the present toe wall. Based on the distribution of and cross-cutting relationship between intra-slide structures, we propose an emplacement model involving two distinct phases of deformation; (i) bulk shortening, parallel to the overall SE-directed emplacement direction, accommodated by the formation of NE-trending symmetric pop-up blocks bound by fore-thrusts and back-thrusts; and (ii) the development of NW-trending sinistral shear zones that offsets the earlier formed shortening structures, and which possibly formed due a spatial variations the evolving rock strength as the flow arrested, resulting in intra-slide flow cells. We infer the basal shear surface or zone incrementally propagated downdip ahead of the developing slide mass, with distal contractional structures being the expression of rather cryptic, updip sliding of the entire sediment mass. Our study demonstrates the value of using 3D seismic reflection data to study the structure and emplacement kinematics of slides, and the complex strains that can arise due to temporal and spatial variations in sediment rheology.
{"title":"Strike-slip overprinting of initial co-axial shortening within the toe region of a submarine landslide: a case study from the Angoche Basin, offshore Mozambique.","authors":"C. Abu, C. Jackson, M. Francis","doi":"10.31223/x5g315","DOIUrl":"https://doi.org/10.31223/x5g315","url":null,"abstract":"Submarine landslides (slides) are some of the most voluminous sediment gravity-flows on Earth and they dominate the stratigraphic record of many subaqueous basins. The general kinematics and internal structure of slides are relatively well-understood, although the way in which they increase in volume and internally deformed as they evolve, and how these processes relate to the development of their basal (shear) surface, remains largely unknown. We here use three high-resolution 3D seismic surveys (two broadband time-migrated seismic reflection datasets and a depth-migrated volume) from the Angoche Basin, offshore Mozambique to undertake detailed mapping and intra-slide strain analysis of a shallowly buried, large, and thus well-imaged submarine landslide (c. 530 km3). We also provide detailed documentation of the along-strike variations in the structural style and evolution of the toe region, and how these relate to the overall emplacement of the slide. Seismic attribute analysis image several key kinematic indicators, including broadly NW-trending (i.e., flow-parallel) lateral margins, longitudinal shears, and sub-orthogonal shears in the main body of the deposit, and broadly NE-trending (i.e., flow-normal) symmetric pop-up blocks in the toe region. The slide exhibits varying degrees of frontal emergence along strike, displaying a single frontal (toe) wall in the SW to a more complex, stair-step geometry in the NE. Basal grooves are noticeably absent, with a key observation being that contractional structures are locally observed c. 7 km downdip of the present toe wall. Based on the distribution of and cross-cutting relationship between intra-slide structures, we propose an emplacement model involving two distinct phases of deformation; (i) bulk shortening, parallel to the overall SE-directed emplacement direction, accommodated by the formation of NE-trending symmetric pop-up blocks bound by fore-thrusts and back-thrusts; and (ii) the development of NW-trending sinistral shear zones that offsets the earlier formed shortening structures, and which possibly formed due a spatial variations the evolving rock strength as the flow arrested, resulting in intra-slide flow cells. We infer the basal shear surface or zone incrementally propagated downdip ahead of the developing slide mass, with distal contractional structures being the expression of rather cryptic, updip sliding of the entire sediment mass. Our study demonstrates the value of using 3D seismic reflection data to study the structure and emplacement kinematics of slides, and the complex strains that can arise due to temporal and spatial variations in sediment rheology.","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134016006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-30DOI: 10.1190/SEGAM2020-3425780.1
R. Michelena, K. Godbey, M. Uland, Patricia E. Rodrigues
Petrophysical modeling in unconventional reservoirs requires tools that take into account their complex mineral composition and lack of log information necessary to resolve this complexity in detail. We pose the estimation of properties of mineral constituents of the rock as a stochastic nonlinear optimization problem where a genetic algorithm (a type of algorithm in the artificial intelligence spectrum) replaces the time-consuming, manual trial-and-error process of adjusting properties and fitting the input logs in conventional multimineral analysis. The method requires interpretative inputs based on prior knowledge and experience, but such inputs are provided in the form of ranges instead of single property values, facilitating the work of the analyst. By testing adaptively thousands of solutions and considerably reducing the time needed to fit the input logs with a consistent set of properties, it becomes then possible to test other scenarios of input data and constituents, quantify the uncertainty and non-uniqueness of individual parameters, and shed light upon higher-level petrophysical questions such as spatial variations in kerogen maturity, water resistivity, or clay composition. We illustrate the use of the methodology to estimate fractions of constituents for the mineralogically complex Bakken Formation and to estimate variations of thermal maturity with depth in the Marcellus, shale gas Formation.
{"title":"Petrophysical multimineral analysis using genetic optimization to solve complex mineral composition in unconventional reservoirs","authors":"R. Michelena, K. Godbey, M. Uland, Patricia E. Rodrigues","doi":"10.1190/SEGAM2020-3425780.1","DOIUrl":"https://doi.org/10.1190/SEGAM2020-3425780.1","url":null,"abstract":"Petrophysical modeling in unconventional reservoirs requires tools that take into account their complex mineral composition and lack of log information necessary to resolve this complexity in detail. We pose the estimation of properties of mineral constituents of the rock as a stochastic nonlinear optimization problem where a genetic algorithm (a type of algorithm in the artificial intelligence spectrum) replaces the time-consuming, manual trial-and-error process of adjusting properties and fitting the input logs in conventional multimineral analysis. The method requires interpretative inputs based on prior knowledge and experience, but such inputs are provided in the form of ranges instead of single property values, facilitating the work of the analyst. By testing adaptively thousands of solutions and considerably reducing the time needed to fit the input logs with a consistent set of properties, it becomes then possible to test other scenarios of input data and constituents, quantify the uncertainty and non-uniqueness of individual parameters, and shed light upon higher-level petrophysical questions such as spatial variations in kerogen maturity, water resistivity, or clay composition. We illustrate the use of the methodology to estimate fractions of constituents for the mineralogically complex Bakken Formation and to estimate variations of thermal maturity with depth in the Marcellus, shale gas Formation.","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115371967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-30DOI: 10.1190/SEGAM2020-3423261.1
Hendratta Ali, N. I. Konfor, J. Atangana, A. Magha, Arkhat Kalbekov, M. Pohl, M. Prasad, H. Agbogun, Mbida Yem, E. Atekwana
{"title":"Water everywhere but how much is there to drink? A geophysical investigation and water quality assessment in a rural community: Nkoteng, Cameroon","authors":"Hendratta Ali, N. I. Konfor, J. Atangana, A. Magha, Arkhat Kalbekov, M. Pohl, M. Prasad, H. Agbogun, Mbida Yem, E. Atekwana","doi":"10.1190/SEGAM2020-3423261.1","DOIUrl":"https://doi.org/10.1190/SEGAM2020-3423261.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115732083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-30DOI: 10.1190/SEGAM2020-3427254.1
A. Dhara, C. Bagaini
{"title":"Deep learning for seismic image registration","authors":"A. Dhara, C. Bagaini","doi":"10.1190/SEGAM2020-3427254.1","DOIUrl":"https://doi.org/10.1190/SEGAM2020-3427254.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123042591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-30DOI: 10.1190/SEGAM2020-W6-04.1
Yike Liu, B. He, Yingcai Zheng
{"title":"Full-waveform inversion using multiples and primaries","authors":"Yike Liu, B. He, Yingcai Zheng","doi":"10.1190/SEGAM2020-W6-04.1","DOIUrl":"https://doi.org/10.1190/SEGAM2020-W6-04.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124438134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-30DOI: 10.1190/SEGAM2020-3427595.1
Junxiao Li, K. Xin, Jian Sun, Farah Syazana
{"title":"A new qP-wave approximation in TTI media and its reverse time migration","authors":"Junxiao Li, K. Xin, Jian Sun, Farah Syazana","doi":"10.1190/SEGAM2020-3427595.1","DOIUrl":"https://doi.org/10.1190/SEGAM2020-3427595.1","url":null,"abstract":"","PeriodicalId":117371,"journal":{"name":"Seg Technical Program Expanded Abstracts","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116712591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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