83rd EAGE Annual Conference & Exhibition最新文献

Pioneering Subsurface Data Management Studio and Asset Retirement Obligation Retrenchment in Upstream South Sumatra Region, Indonesia 印度尼西亚南苏门答腊上游地区开创性地下数据管理工作室和资产退休义务缩减

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-09-26 DOI: 10.3997/2214-4609.202210638

A. Permana, A. Sulaksono, N. Hikmah, I. Dwiyono, R. Pratama, Y. Gustian, P. Suseno, S. Parsaulian

{"title":"Pioneering Subsurface Data Management Studio and Asset Retirement Obligation Retrenchment in Upstream South Sumatra Region, Indonesia","authors":"A. Permana, A. Sulaksono, N. Hikmah, I. Dwiyono, R. Pratama, Y. Gustian, P. Suseno, S. Parsaulian","doi":"10.3997/2214-4609.202210638","DOIUrl":"https://doi.org/10.3997/2214-4609.202210638","url":null,"abstract":"\u0000 According to the geoscientist work profile in Oil & Gas Journal, 1998, inadequate data management practice has caused 60% proportion of the time to be spent for data searching and compilation, it has consequently reduced time for appropriate subsurface analysis. The oil and gas industry in the South Sumatra region is categorized as a matured working area and always becoming a challenge to operate efficiently, not only because of well-developed fields and depleted reservoirs, but also commonly deals with a huge amount of old raw data set, either well coordinates, seismic, trajectory, or log data, even data duplication itself. However, since its first discovery in 1896, the South Sumatra region has already transformed into one of the most productive basins in Indonesia until the present through immense exploration and development activities. Additionally, more than 4000 wells have been drilled in 86 oil fields of the South Sumatra block within an 18,181 km2 working area. Massive operational jobs such as drilling programs, workover, and well intervention involved a lot of subsurface data. Invalid data has proven a serious problem that caused several operational failures and enormous financial losses. Proper implementation of subsurface data management for the last several years has generated significant progress for future company milestones.","PeriodicalId":223218,"journal":{"name":"83rd EAGE Annual Conference & Exhibition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126588320","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}

引用次数: 0

First-Arrival Traveltime and Slope Tomography in Tilted Anisotropic Media with Undulant Topography 起伏地形倾斜各向异性介质的初到行时和斜率层析成像

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-08-15 DOI: 10.3997/2214-4609.202210684

X. Zhou, S. Serge, H. Lan, L. Chen, O. Stephane

引用次数: 0

Data Driven Reservoir Properties Estimation Using Maz Towed Multisensor Streamer Seismic: a Norwegian Case Study 使用Maz拖曳多传感器拖缆地震进行数据驱动的储层属性估计:挪威案例研究

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-08-15 DOI: 10.3997/2214-4609.202210469

C. Reiser, R. Ruiz

引用次数: 0

Water Column Corrections, Joint Water Velocity Inversion for 4D Marine Surveys 四维海洋测量水柱校正、联合水体速度反演

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-08-15 DOI: 10.3997/2214-4609.202210729

D. Lecerf, M. Lange, A. Oates, J. Kumar

{"title":"Water Column Corrections, Joint Water Velocity Inversion for 4D Marine Surveys","authors":"D. Lecerf, M. Lange, A. Oates, J. Kumar","doi":"10.3997/2214-4609.202210729","DOIUrl":"https://doi.org/10.3997/2214-4609.202210729","url":null,"abstract":"Water column variations are an important source of non-repeatability in time-lapse marine surveys. In a deep water context, the physical property variations within the water layers can generate significant time-shifts between repeated time-lapse seismic data. We present a new methodology for estimating water velocity changes and correcting the 4D seismic datasets. Each sail line is migrated independently and Common Depth Point (CDP) gathers are produced for the overburden along a subsurface strip for both vintages. The 4D approach consists of performing cross-correlations using collocated CDPs for each sail lines pair. It creates water bottom “cross-image CDP gathers”. The cross-image CDP curvature along offsets is used to compute the water velocity difference between the two vintages. Once a water velocity is inverted for each sail line, the kinematic correction is performed on the pre-migrated datasets. The main difference with conventional approaches is the simultaneous usage of both 4D datasets for estimating the water velocity changes and therefore minimizing the seismic difference in the overburden. The methodology is significantly beneficial for deep-water 4D acquisitions. The correction for such small environmental variations improves the time-lapse data repeatability and is part of the effort for providing high resolution 4D images.","PeriodicalId":223218,"journal":{"name":"83rd EAGE Annual Conference & Exhibition","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128186661","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}

引用次数: 0

Integrated Workflow for Characterization of CO2 Subsurface Storage Sites 二氧化碳地下储存地点的集成工作流程表征

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-08-15 DOI: 10.3997/2214-4609.202210978

N. Pernin, C. Reiser, E. Mueller

引用次数: 0

Q-Compensated Least-Squares Reverse Time Migration with Velocity-Anisotropy Correction Based on the First-Order Velocity-Pressure Equations 基于一阶速度-压力方程的速度-各向异性校正的q补偿最小二乘逆时偏移

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-08-09 DOI: 10.3997/2214-4609.202210629

J. Zhu, Y. Qu

{"title":"Q-Compensated Least-Squares Reverse Time Migration with Velocity-Anisotropy Correction Based on the First-Order Velocity-Pressure Equations","authors":"J. Zhu, Y. Qu","doi":"10.3997/2214-4609.202210629","DOIUrl":"https://doi.org/10.3997/2214-4609.202210629","url":null,"abstract":"Anisotropy and Q attenuation bring great challenges to seismic wave migration. On migrated images, anisotropy creates structural and positioning errors, and Q attenuation leads to weak amplitudes and misplacement of reflectors. A 2D Q-compensated least-squares reverse time migration with velocity-anisotropy correction ( QLSRTM-VA) is proposed through the construction of velocity-anisotropic Q-compensated forward modeling, Q-compensated adjoint, and Q-attenuated demigration operators to simultaneously correct velocity-anisotropy and Q-attenuation in the migration process. The preceding operators are derived using first-order velocity-anisotropic viscoacoustic quasi-differential wave equations with variable densities, which are stable, capable of conveniently dealing with variable density media and are easy to transform between velocity-anisotropic Q-compensation and Q-attenuation versions. As exemplified by two synthetic and field data sets, our QLSRTM-VA method increases the imaging resolution, signal-to-noise ratio, and amplitude preservation in deep regions. Our method is capable of producing better images than viscoacoustic isotropic least-squares reverse time migration (LSRTM) and acoustic anisotropic LSRTM.","PeriodicalId":223218,"journal":{"name":"83rd EAGE Annual Conference & Exhibition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129283856","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}

引用次数: 4

Horizon Auto-Picking with Quantitative Uncertainty Evaluation by Using a Modified Vq-Vae Network 基于改进Vq-Vae网络的定量不确定度自动选取

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-07-29 DOI: 10.3997/2214-4609.202210311

C. Yuan, M. Su, C. Ni, Xingye Liu, Yunze Xu, Xiaohui Cui

{"title":"Horizon Auto-Picking with Quantitative Uncertainty Evaluation by Using a Modified Vq-Vae Network","authors":"C. Yuan, M. Su, C. Ni, Xingye Liu, Yunze Xu, Xiaohui Cui","doi":"10.3997/2214-4609.202210311","DOIUrl":"https://doi.org/10.3997/2214-4609.202210311","url":null,"abstract":"\u0000 In this paper, we propose a novel approach of deep-learning-based seismic horizon auto-picking that introduces a modified vector quantized variational autoencoder (VQ-VAE) framework to improve the accuracy of seismic horizon interpretation and, for the first time, quantitatively evaluate the uncertainty of the auto-picked horizon by exploiting the concept of entropy. Compared with the conventional VQ-VAE approach, the proposed method not only modifies the VQ-VAE model with more deep-learning channels at each layer of the network to enhance the performance of horizon auto-picking within the VQ-VAE framework, but also extends the 1D seismic labels with more continuous samplings within a single trace to boost the stability of auto-picked horizon in geologically complex settings and also significantly suppress the resulting uncertainty. To further improve the resulting accuracy in geologically complex settings, we introduce the directional structure tensor to extract a more reliable initial horizon and, moreover, a dilated horizon searching strategy to extend the capacity of the proposed method in dealing with the large fault displacement and reducing the computational cost simultaneously. Additionally, the resulting uncertainty quantitatively measured by entropy can also serve as an effective indicator to enable a further refinement of the auto-picked result accordingly. Both 2D example and 3D field applications are carried out to validate the effectiveness of the proposed method.","PeriodicalId":223218,"journal":{"name":"83rd EAGE Annual Conference & Exhibition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121239580","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}

引用次数: 0

Application of Asymptotic Solution of Helmholtz Equation in Full Waveform Inversion Helmholtz方程渐近解在全波形反演中的应用

83rd EAGE Annual Conference & Exhibition Pub Date : 2022-05-18 DOI: 10.3997/2214-4609.202210100

K. Gadylshin, D. Neklyudov, M. Protasov

引用次数: 0

A Novel Classification System and Database for Faults and Tectonic Features in the Netherlands 荷兰断裂与构造特征的新分类系统和数据库

83rd EAGE Annual Conference & Exhibition Pub Date : 2021-10-18 DOI: 10.3997/2214-4609.202112767

J. Veen, M. D. Dulk, S. V. Gessel, R. V. Ede, H. Doornenbal, J. Hettelaar, E. Hintersberger

引用次数: 0

The Application of Wavelet Transform Based on Tk Energy in Reservoir Description 基于Tk能量的小波变换在储层描述中的应用

83rd EAGE Annual Conference & Exhibition Pub Date : 2017-08-17 DOI: 10.1190/SEGAM2017-17752087.1

D. Hou, Donghong Zhou, Zhijun Zhang, D. Guan, Cai Li, Yao Li, Benhou Jiang, Ye Zhao

引用次数: 0

83rd EAGE Annual Conference &amp; Exhibition最新文献

83rd EAGE Annual Conference & Exhibition最新文献