Pub Date : 2023-12-01DOI: 10.3997/1365-2397.fb2023099
C. Hanton, Venkatesh Anantharamu
{"title":"Automating the Data Flow — How AI and ML can Reimagine Subsurface Data Management","authors":"C. Hanton, Venkatesh Anantharamu","doi":"10.3997/1365-2397.fb2023099","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023099","url":null,"abstract":"","PeriodicalId":35692,"journal":{"name":"First Break","volume":"102 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138609142","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 : 2023-12-01DOI: 10.3997/1365-2397.fb2023098
Frank Richards, Mark Cowgill, Megan Rayner
{"title":"Applied Fault Topology: Understanding Connectivity and Uncertainty of Fault Systems that Define and Affect Commercial and Environmental Projects","authors":"Frank Richards, Mark Cowgill, Megan Rayner","doi":"10.3997/1365-2397.fb2023098","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023098","url":null,"abstract":"","PeriodicalId":35692,"journal":{"name":"First Break","volume":"113 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138609580","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 : 2023-12-01DOI: 10.3997/1365-2397.fb2023100
Kristy DeMarco
{"title":"Streamlining Energy and Production Data Management from Field to Processing","authors":"Kristy DeMarco","doi":"10.3997/1365-2397.fb2023100","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023100","url":null,"abstract":"","PeriodicalId":35692,"journal":{"name":"First Break","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138613344","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 : 2023-12-01DOI: 10.3997/1365-2397.fb2023102
Jill Lewis, Shawn New, Joel Allard, Victor Ancira
{"title":"How the Latest SEG-Y Revision will Improve Data Management","authors":"Jill Lewis, Shawn New, Joel Allard, Victor Ancira","doi":"10.3997/1365-2397.fb2023102","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023102","url":null,"abstract":"","PeriodicalId":35692,"journal":{"name":"First Break","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138619067","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 : 2023-12-01DOI: 10.3997/1365-2397.fb2023104
N. Hodgson, K. Rodriguez, Helen Debenham, Lauren Found
{"title":"Affordably Making the Invisible Unmissable","authors":"N. Hodgson, K. Rodriguez, Helen Debenham, Lauren Found","doi":"10.3997/1365-2397.fb2023104","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023104","url":null,"abstract":"","PeriodicalId":35692,"journal":{"name":"First Break","volume":"74 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138622850","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}
In marine seismic surveys, data acquisition typically involves an end-on shooting geometry. While the Reverse Time Migration (RTM) method applied to end-on shot gathers often yields high-quality images, there are instances where certain dips may be inadequately represented or even missing in the migrated section. This paper introduces an efficient utilisation of the well-established principle of reciprocity to demonstrate the creation of a Pseudo Split-Spread (PSS) shot gather from existing one-sided offset shot gathers. Additionally, we illustrate that employing generated PSS shot gathers for RTM imaging of dipping events results in significant improvements compared to using recorded end-on shot gathers for both isotropic and anisotropic Vertically Transverse Isotropic (VTI) media. The proposed approach has been investigated in depth for its underlying methodology and additional advantages. The efficacy of this proposed RTM approach is substantiated through successful testing with synthetic and field data examples using isotropic and anisotropic VTI media.
{"title":"Enhanced RTM Imaging of Marine Streamer Data Using Pseudo Split-Spread (PSS) Shot Gathers","authors":"Richa Rastogi, Abhishek Srivastava, Bhushan Mahajan, Monika Gawade, Suhas Phadke, Saheb Ghosh","doi":"10.3997/1365-2397.fb2023095","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023095","url":null,"abstract":"In marine seismic surveys, data acquisition typically involves an end-on shooting geometry. While the Reverse Time Migration (RTM) method applied to end-on shot gathers often yields high-quality images, there are instances where certain dips may be inadequately represented or even missing in the migrated section. This paper introduces an efficient utilisation of the well-established principle of reciprocity to demonstrate the creation of a Pseudo Split-Spread (PSS) shot gather from existing one-sided offset shot gathers. Additionally, we illustrate that employing generated PSS shot gathers for RTM imaging of dipping events results in significant improvements compared to using recorded end-on shot gathers for both isotropic and anisotropic Vertically Transverse Isotropic (VTI) media. The proposed approach has been investigated in depth for its underlying methodology and additional advantages. The efficacy of this proposed RTM approach is substantiated through successful testing with synthetic and field data examples using isotropic and anisotropic VTI media.","PeriodicalId":35692,"journal":{"name":"First Break","volume":"20 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135514457","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 : 2023-11-01DOI: 10.3997/1365-2397.fb2023092
Alexey Dobrovolskiy
Preview this article: Water Bodies Data Collection Using UAV: UXO Search and Bathymetry, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/fb/41/11/fb2023092-1.gif
{"title":"Water Bodies Data Collection Using UAV: UXO Search and Bathymetry","authors":"Alexey Dobrovolskiy","doi":"10.3997/1365-2397.fb2023092","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023092","url":null,"abstract":"Preview this article: Water Bodies Data Collection Using UAV: UXO Search and Bathymetry, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/fb/41/11/fb2023092-1.gif","PeriodicalId":35692,"journal":{"name":"First Break","volume":"40 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135510660","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 : 2023-11-01DOI: 10.3997/1365-2397.fb2023094
Tim Bunting
Preview this article: Autonomous Vehicles for Deployment and Recovery of Seismic Ocean Bottom Nodes, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/fb/41/11/fb2023094-1.gif
预览本文:用于部署和恢复地震海底节点的自动驾驶车辆,Page 1 of 1 <上一页|下一页> /docserver/ Preview /fulltext/fb/41/11/fb2023094-1.gif
{"title":"Autonomous Vehicles for Deployment and Recovery of Seismic Ocean Bottom Nodes","authors":"Tim Bunting","doi":"10.3997/1365-2397.fb2023094","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023094","url":null,"abstract":"Preview this article: Autonomous Vehicles for Deployment and Recovery of Seismic Ocean Bottom Nodes, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/fb/41/11/fb2023094-1.gif","PeriodicalId":35692,"journal":{"name":"First Break","volume":"25 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135514658","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 : 2023-11-01DOI: 10.3997/1365-2397.fb2023093
Nicolas Tellier, Philippe Herrmann
Despite a recovery in the number of towed-streamer surveys being conducted, OBN (Ocean Bottom Node) seismic projects continue to take an increasing market share over towed-streamer surveys. In OBN acquisition, each node is equipped with a pressure sensor (hydrophone) and three motion sensors (typically, geophones). The nearly-a-century-old geophone technology has, however, certain inherent shortcomings that degrade the recorded signal. Geophone performance deviates from reference specifications due to manufacturing tolerances, ageing and changes in temperature. As an example, for 15-Hz omnitilt geophones, as commonly used in OBN acquisitions, the variation in response reaches 3 dB in amplitude and 10 degrees in phase within their range of manufacturing tolerances. These uncertainties in sensor response prove particularly difficult to model and correct for in practice and result in final data sensor artefacts. The insensitivity of geophones to the gravity field also requires the use of additional tilt meters for the verticalisation of the 3C with resulting issues related to the relative orientations of these two pieces of equipment. Today, MEMS (Micro-Electromechanical Systems)-based digital seismic accelerometers have proved to be the high-fidelity alternative to geophones. Their specifications are not affected by temperature, ageing or manufacturing tolerances, making the recorded signal accurate in phase and amplitude with the seismic signal over the entire seismic bandwidth. As MEMS can detect the gravity vector, the integration of this sensing technology into OBN has demonstrated that 3C MEMS provide, without pre-processing, seismic signal with true verticality, and a vector fidelity error (error in orthogonality between the three sensors) that is an order of magnitude lower than for 3C geophones. The excellent low-frequency performance of the latest, third-generation MEMS is also ideal for reaping the full benefit of novel low-frequency sources (Ronen 2017), and in this way pushing back further the limits of FWI. This, along with other MEMS properties, makes this sensor a strong driver for the growth of OBN acquisition – especially for sparse or blended acquisition, where sensor fidelity matters more than ever. At the time of writing, the world’s largest OBN survey is continuing in the Middle East and is starting to deliver a promising dataset from the 23,000 MEMS-based OBNs deployed. Observations from this mega-survey, as well as from a previous experimental survey that includes direct comparisons with geophone-based OBN, are presented and discussed in this article.
{"title":"MEMS-based OBN: Lessons Learnt from the Largest OBN Survey Worldwide","authors":"Nicolas Tellier, Philippe Herrmann","doi":"10.3997/1365-2397.fb2023093","DOIUrl":"https://doi.org/10.3997/1365-2397.fb2023093","url":null,"abstract":"Despite a recovery in the number of towed-streamer surveys being conducted, OBN (Ocean Bottom Node) seismic projects continue to take an increasing market share over towed-streamer surveys. In OBN acquisition, each node is equipped with a pressure sensor (hydrophone) and three motion sensors (typically, geophones). The nearly-a-century-old geophone technology has, however, certain inherent shortcomings that degrade the recorded signal. Geophone performance deviates from reference specifications due to manufacturing tolerances, ageing and changes in temperature. As an example, for 15-Hz omnitilt geophones, as commonly used in OBN acquisitions, the variation in response reaches 3 dB in amplitude and 10 degrees in phase within their range of manufacturing tolerances. These uncertainties in sensor response prove particularly difficult to model and correct for in practice and result in final data sensor artefacts. The insensitivity of geophones to the gravity field also requires the use of additional tilt meters for the verticalisation of the 3C with resulting issues related to the relative orientations of these two pieces of equipment. Today, MEMS (Micro-Electromechanical Systems)-based digital seismic accelerometers have proved to be the high-fidelity alternative to geophones. Their specifications are not affected by temperature, ageing or manufacturing tolerances, making the recorded signal accurate in phase and amplitude with the seismic signal over the entire seismic bandwidth. As MEMS can detect the gravity vector, the integration of this sensing technology into OBN has demonstrated that 3C MEMS provide, without pre-processing, seismic signal with true verticality, and a vector fidelity error (error in orthogonality between the three sensors) that is an order of magnitude lower than for 3C geophones. The excellent low-frequency performance of the latest, third-generation MEMS is also ideal for reaping the full benefit of novel low-frequency sources (Ronen 2017), and in this way pushing back further the limits of FWI. This, along with other MEMS properties, makes this sensor a strong driver for the growth of OBN acquisition – especially for sparse or blended acquisition, where sensor fidelity matters more than ever. At the time of writing, the world’s largest OBN survey is continuing in the Middle East and is starting to deliver a promising dataset from the 23,000 MEMS-based OBNs deployed. Observations from this mega-survey, as well as from a previous experimental survey that includes direct comparisons with geophone-based OBN, are presented and discussed in this article.","PeriodicalId":35692,"journal":{"name":"First Break","volume":"44 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135509607","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}