Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201900763
Z. Gao, Z. Pan, J. Gao, Z. Xu
{"title":"Large-Dimensional Seismic Inversion Based on Global Optimization and Autoencoder","authors":"Z. Gao, Z. Pan, J. Gao, Z. Xu","doi":"10.3997/2214-4609.201900763","DOIUrl":"https://doi.org/10.3997/2214-4609.201900763","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76295624","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 : 2019-06-03DOI: 10.3997/2214-4609.201901223
T. Wang, Y. Xie, M. Wang, Y. Guo, S. Wu, X. Ding, S. Wolfarth, Y. Supriatna, P. Santoso
{"title":"Enhance Dynamic-Warping for FWI to Mitigate Cycle-Skipping","authors":"T. Wang, Y. Xie, M. Wang, Y. Guo, S. Wu, X. Ding, S. Wolfarth, Y. Supriatna, P. Santoso","doi":"10.3997/2214-4609.201901223","DOIUrl":"https://doi.org/10.3997/2214-4609.201901223","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76457813","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 : 2019-06-03DOI: 10.3997/2214-4609.201901495
J. Wang, C. Yao, Z. Li, Q. Liu, Y. Zheng
{"title":"Deep Structure of the Gangdese Batholith in Southern Tibet Constrained by Aeromagnetic Anomaly","authors":"J. Wang, C. Yao, Z. Li, Q. Liu, Y. Zheng","doi":"10.3997/2214-4609.201901495","DOIUrl":"https://doi.org/10.3997/2214-4609.201901495","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"22 6S 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76519549","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 : 2019-06-03DOI: 10.3997/2214-4609.201901254
C. Ward, P. Mackintosh, Ø. Clausen, M. Ackers
Summary This paper will present Spirit Energy's recent development drilling results from the Oda oil field in the Norwegian North Sea. The development is located on the flank of a large salt diapir and the wells calibrated the seismic response and the structural configuration of the salt flank.
{"title":"Sub-Seismic Structural Observations Adjacent to a Salt Diapir: The Oda Field, Norwegian North Sea","authors":"C. Ward, P. Mackintosh, Ø. Clausen, M. Ackers","doi":"10.3997/2214-4609.201901254","DOIUrl":"https://doi.org/10.3997/2214-4609.201901254","url":null,"abstract":"Summary This paper will present Spirit Energy's recent development drilling results from the Oda oil field in the Norwegian North Sea. The development is located on the flank of a large salt diapir and the wells calibrated the seismic response and the structural configuration of the salt flank.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"313 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76222352","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 : 2019-06-03DOI: 10.3997/2214-4609.201901172
F. Sun, J. Gao, B. Zhang, Z. Wang, N. Liu
Summary Traditional coherence algorithms most rely on the basic assumption that the relationship between seismic traces is linear and obeys Gaussian distribution. However, in practice, correlation between seismic traces is usually nonlinear, and the seismic traces are non-Gaussian signals. The canonical correlation analysis (CCA) cannot describe the similarity between adjacent seismic traces in detail. To overcome this problem and improve the resolution and robustness of the coherence algorithm, we introduce the kernelized correlation instead of the linear correlation in the C3 algorithm. Note that the kernelized correlation is a generalized correlation with various kernel functions. Then, we discuss how to choose the appropriate kernel function in detail. To demonstrate the validity of the proposed algorithm, we apply it to field data using different kernels. The results demonstrate the effectiveness of the proposed algorithm to describe geological discontinuity and heterogeneity, such as fluvial channels and faults.
{"title":"The Generalized Coherence Algorithm on Seismic Data Based on the Kernel Function","authors":"F. Sun, J. Gao, B. Zhang, Z. Wang, N. Liu","doi":"10.3997/2214-4609.201901172","DOIUrl":"https://doi.org/10.3997/2214-4609.201901172","url":null,"abstract":"Summary Traditional coherence algorithms most rely on the basic assumption that the relationship between seismic traces is linear and obeys Gaussian distribution. However, in practice, correlation between seismic traces is usually nonlinear, and the seismic traces are non-Gaussian signals. The canonical correlation analysis (CCA) cannot describe the similarity between adjacent seismic traces in detail. To overcome this problem and improve the resolution and robustness of the coherence algorithm, we introduce the kernelized correlation instead of the linear correlation in the C3 algorithm. Note that the kernelized correlation is a generalized correlation with various kernel functions. Then, we discuss how to choose the appropriate kernel function in detail. To demonstrate the validity of the proposed algorithm, we apply it to field data using different kernels. The results demonstrate the effectiveness of the proposed algorithm to describe geological discontinuity and heterogeneity, such as fluvial channels and faults.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86891317","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 : 2019-06-03DOI: 10.3997/2214-4609.201901356
Z. Zhu, D. Cao, B. Wu
{"title":"Seismic High Amplitude Noise Attenuation Based on the Deep Learning Method","authors":"Z. Zhu, D. Cao, B. Wu","doi":"10.3997/2214-4609.201901356","DOIUrl":"https://doi.org/10.3997/2214-4609.201901356","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87553883","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 : 2019-06-03DOI: 10.3997/2214-4609.201900777
D. Lokshtanov, J. Fjellanger, R. Anisimov, R. Davletkhanov, D. Finikov
{"title":"Efficient Suppression of Multiples in the Valemon-Kvitebørn Reprocessing and Imaging Project","authors":"D. Lokshtanov, J. Fjellanger, R. Anisimov, R. Davletkhanov, D. Finikov","doi":"10.3997/2214-4609.201900777","DOIUrl":"https://doi.org/10.3997/2214-4609.201900777","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87747721","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 : 2019-06-03DOI: 10.3997/2214-4609.201901062
R. Prajapati, U. Singh, M. Abdullahi
{"title":"Identification of Stratigraphic Boundaries of a Well Using Wavelet and Fourier Transform","authors":"R. Prajapati, U. Singh, M. Abdullahi","doi":"10.3997/2214-4609.201901062","DOIUrl":"https://doi.org/10.3997/2214-4609.201901062","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87987343","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 : 2019-06-03DOI: 10.3997/2214-4609.201901247
M. Farhadiroushan, T. Parker, S. Shatalin, A. Gillies, Z. Chen, A. Clarke, G. Naldrett
Summary Distributed Acoustic Sensing (DAS) technology enables advanced geophysical measurement methods, where the fibre optic cable is deployed as a dense, wide-aperture phase-array sensor in novel configurations. A sensing system has recently been developed that combines an engineered fiber with bright scatter centers with a low-noise, wide dynamic-range optoelectronics DAS interrogator. This enhanced DAS with engineered fiber offers a 20dB (100x) improvement in sensitivity and dynamic range compared to that achieved with standard fiber. The new DAS technology seeks to disrupt conventional geophysical surveying methods, and so enable the realisation of new applications. In unconventional wells, in addition to seismic and microseismic measurements, the improved low frequency response of the DAS system, down to the milli-Hertz level, is used to monitor hydraulically induced strain effects. In offshore applications, the permanent installation of the fiber optic along production and injection wells is enabling more frequent and cost-effective seismic data to be acquired. The next challenge is stepping out to subsea wells. We present some initial lab results demonstrating the benefits of the engineered fiber for advanced seismic acquisition in long-tie back subsea wells using only surface optoelectronics.
{"title":"Advanced Geophysical Measurement Methods Using Engineered Fiber Optic Acoustic Sensor","authors":"M. Farhadiroushan, T. Parker, S. Shatalin, A. Gillies, Z. Chen, A. Clarke, G. Naldrett","doi":"10.3997/2214-4609.201901247","DOIUrl":"https://doi.org/10.3997/2214-4609.201901247","url":null,"abstract":"Summary Distributed Acoustic Sensing (DAS) technology enables advanced geophysical measurement methods, where the fibre optic cable is deployed as a dense, wide-aperture phase-array sensor in novel configurations. A sensing system has recently been developed that combines an engineered fiber with bright scatter centers with a low-noise, wide dynamic-range optoelectronics DAS interrogator. This enhanced DAS with engineered fiber offers a 20dB (100x) improvement in sensitivity and dynamic range compared to that achieved with standard fiber. The new DAS technology seeks to disrupt conventional geophysical surveying methods, and so enable the realisation of new applications. In unconventional wells, in addition to seismic and microseismic measurements, the improved low frequency response of the DAS system, down to the milli-Hertz level, is used to monitor hydraulically induced strain effects. In offshore applications, the permanent installation of the fiber optic along production and injection wells is enabling more frequent and cost-effective seismic data to be acquired. The next challenge is stepping out to subsea wells. We present some initial lab results demonstrating the benefits of the engineered fiber for advanced seismic acquisition in long-tie back subsea wells using only surface optoelectronics.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88111663","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 : 2019-06-03DOI: 10.3997/2214-4609.201900743
F. Geffroy, Pedro Correia, H. Binet, J. Chautru, D. Renard, N. Nosjea-Gorgeu
Summary Faults are objects interpreted from seismic data that are often difficult to characterize. Not only the type of a fault can appear different depending on the domain the modeler is working on (time or depth), but accurate shape mapping often extends below the level of coherent seismic data. This proves especially impactful when we consider that simple errors in the fault-network characterization can render a subsurface model useless in terms of its flow properties and provide erroneous values for volumes of reserves. Nevertheless, in absence of proper technology, depth conversion workflows do not account for fault uncertainties, instead relying on a single deterministic interpretation. This paper presents a new methodology that considers positional fault uncertainty in time-to-depth conversion workflows. By considering different realizations of a fault, the target surface is dynamically adapted to this new position and can be used to update further volumetric computations. The proposed methodology can be fully automated and results in a more complete exploration of the uncertainty space regarding fault interpretation.
{"title":"Integration of Fault Location Uncertainty in Time to Depth Conversion","authors":"F. Geffroy, Pedro Correia, H. Binet, J. Chautru, D. Renard, N. Nosjea-Gorgeu","doi":"10.3997/2214-4609.201900743","DOIUrl":"https://doi.org/10.3997/2214-4609.201900743","url":null,"abstract":"Summary Faults are objects interpreted from seismic data that are often difficult to characterize. Not only the type of a fault can appear different depending on the domain the modeler is working on (time or depth), but accurate shape mapping often extends below the level of coherent seismic data. This proves especially impactful when we consider that simple errors in the fault-network characterization can render a subsurface model useless in terms of its flow properties and provide erroneous values for volumes of reserves. Nevertheless, in absence of proper technology, depth conversion workflows do not account for fault uncertainties, instead relying on a single deterministic interpretation. This paper presents a new methodology that considers positional fault uncertainty in time-to-depth conversion workflows. By considering different realizations of a fault, the target surface is dynamically adapted to this new position and can be used to update further volumetric computations. The proposed methodology can be fully automated and results in a more complete exploration of the uncertainty space regarding fault interpretation.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88388718","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：