Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
Asia (Country)
Adaptive laterally constrained inversion of time-domain electromagnetic data using Hierarchical Bayes
Li, Hai (Chinese Academy of Sciences, Chinese Academy of Sciences) | Di, Qingyun (Chinese Academy of Sciences, Chinese Academy of Sciences) | Li, Keying (Chinese Academy of Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences)
Laterally constrained inversion (LCI) of time-domain electromagnetic (TEM) data is effective in recovering quasi-layered models, particularly in sedimentary environments. By incorporating lateral constraints, LCI enhances the stability of the inverse problem and improves the resolution of stratified interfaces. However, a limitation of the LCI is the recovery of laterally smooth transitions, even in regions unsupported by the available datasets. Therefore, we have developed an adaptive LCI scheme within a Bayesian framework. Our approach introduces user-defined constraints through a multivariate Gaussian prior, where the variances serve as hyperparameters in a Hierarchical Bayes algorithm. By simultaneously sampling the model parameters and hyperparameters, our scheme allows for varying constraints throughout the model space, selectively preserving lateral constraints that align with the available datasets. We demonstrated the effectiveness of our adaptive LCI scheme through a synthetic example. The inversion results showcase the self-adaptive nature of the strength of constraints, yielding models with smooth lateral transitions while accurately retaining sharp lateral interfaces. An application to field TEM data collected in Laizhou, China, supports the findings from the synthetic example. The adaptive LCI scheme successfully images quasi-layered environments and formations with well-defined lateral interfaces. Moreover, the Bayesian inversion provides a measure of uncertainty, allowing for a comprehensive illustration of the confidence in the inversion results.
- Geology > Mineral (0.93)
- Geology > Sedimentary Geology > Depositional Environment (0.34)
- Oceania > Australia > Western Australia > North West Shelf > Carnarvon Basin > Exmouth Plateau > WA-1-R > Scarborough Field (0.99)
- Europe > Norway (0.91)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation > Evaluation of uncertainties (0.93)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (0.79)
- (2 more...)
Embracing a mission of connecting the world of applied geophysics,the Society of Exploration Geophysicists (SEG) is a not-for-profit organization supporting more than 11,000 members from 126 countries. SEG's long-standing tradition of excellence in education, professional development, new business generation, and engagement cultivates a unique community platform that encourages collaboration and thought leadership for the advancement of geophysical science around the world. Headquartered in Houston, TX, SEG has a business office in Tulsa, OK and regional offices in Dubai, UAE and Beijing, China. SEG is a global society that fosters the expert and ethical practice of geophysics in the exploration and development of natural resources, in characterizing the near-surface, and in mitigating earth hazards by inspiring the geophysicists of today and tomorrow.
- North America > United States > Texas > Harris County > Houston (0.30)
- North America > United States > Oklahoma > Tulsa County > Tulsa (0.30)
- Asia > Middle East > UAE > Dubai Emirate > Dubai (0.30)
- Asia > China > Beijing > Beijing (0.30)
- Information Technology > Knowledge Management (0.82)
- Information Technology > Communications > Collaboration (0.82)
Introduction to special section: South China Sea deep structures and tectonics
Zhang, Ruwei (Guangzhou Marine Geological Survey) | Zhang, Baojin (Guangzhou Marine Geological Survey) | Zhu, Hongtao (China University of Geosciences) | Sibuet, Jean-Claude (Ifremer Centre de Brest) | Briais, Anne (Centre National de la Recherche Scientifique) | Wu, Jonny (University of Houston) | Susilohadi, Susilohadi (National Research and Innovation Agency) | Zeng, Hongliu (The University of Texas at Austin) | Chen, Jianxiong (Anadarko Petroleum Corporation) | Zhong, Guangfa (TongJi University)
E-mail: susi021@brin.go.id 8.The University of Texas at Austin, USA. The South China Sea (SCS) is one of the largest Cenozoic marginal seas in the Western Pacific region. This oceanic basin was opened from the southeastern edge of the Asia continent under the interaction of the Eurasian, Indo-Australian, and Philippine Sea-Pacific plates. Therefore, it provides an exceptional natural laboratory to investigate the genesis of marginal seas and to explore plate-tectonic interactions. It is suggested that the deep structural and tectonic characteristics in the SCS reflect the conditions of the formation and geodynamic evolution of the basin.
- Asia > China (1.00)
- North America > United States > Texas > Travis County > Austin (0.26)
If a contest or a division is not held in your assigned region, you can request to present your paper in an assigned alternate region. Every region has only one alternate region. To make an alternate region paper request, or if the alternate region is not holding a contest, please contact spc@spe.org.
- Europe > Croatia (0.21)
- Asia > Indonesia (0.21)
- South America > Brazil > Rio de Janeiro (0.19)
- North America > United States > California (0.19)
More than 1,000 mound structures have been mapped in shallow marine sediments at the Cretaceous Paleogene boundary in the Rub Al-Khali of Saudi Arabia. Mapping utilized 3D reflection seismic data in a 37,000 square kilometer study area. No wells penetrate the mounds themselves. The mounds are at a present-day subsurface depth of approximately 1 km and are convex-up with diameters of 200 400 m and elevation of 10 15 m. The mounds display spatial self-organization with a mean separation of approximately 3.75 km. Comparison with mound populations in other study areas with known spatial distribution statistics and modes of origin indicates that the mound population in this study has the characteristics of fluid escape structures, and they are interpreted here as mud volcanoes. The observation that the mounds occur at the Cretaceous Paleogene boundary demands a singular trigger at that moment in time. We develop a model of seismic energy related mud volcanism mechanism including the Chicxulub asteroid impact as the energy source that accounts for the timing of the mound structures, and a drainage cell model based on producing water wells that provides a mechanism for spatial self-organization into a regular pattern.
- Europe (1.00)
- Asia > Middle East > Saudi Arabia (1.00)
- Africa (1.00)
- Phanerozoic > Cenozoic > Paleogene > Paleocene (0.67)
- Phanerozoic > Mesozoic > Cretaceous > Upper Cretaceous (0.46)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment (1.00)
- Geology > Rock Type > Sedimentary Rock (1.00)
- Geology > Geological Subdiscipline > Volcanology (1.00)
- (2 more...)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation > Well Tie (0.46)
- Oceania > New Zealand > South Island > South Pacific Ocean > Great South Basin (0.99)
- North America > Canada > Saskatchewan > Prairie Evaporite Basin (0.99)
- Europe > Norway > North Sea > Central North Sea > Norwegian-Danish Basin (0.99)
- (6 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
Unsupervised Deep Learning Framework for 5D Seismic Denoising and Interpolation
Saad, Omar M. (National Research Institute of Astronomy and Geophysics (NRIAG), King Abdullah University of Science and Technology (KAUST)) | Helmy, Islam (National Research Institute of Astronomy and Geophysics (NRIAG)) | Chen, Yangkang (The University of Texas at Austin)
We propose an unsupervised framework to reconstruct the missing data from the noisy and incomplete five-dimensional (5D) seismic data. The proposed method comprises two main components: a deep learning network and a projection onto convex sets (POCS) method. The model works iteratively, passing the data between the two components and splitting the data into a group of patches using a patching scheme. Specifically, the patching scheme breaks the input data into small segments which are then reshaped to a vector of one dimension feeding the deep learning model. Afterward, POCS is utilized to optimize the output data from the deep learning model, which is proposed to denoise and interpolate the extracted patches. The proposed deep learning model consists of several blocks, that are, fully connected layers, attention block, and several skip connections. Following this, the output of the POCS algorithm is considered as the input of the deep learning model for the following iteration. The proposed model iteratively works in an unsupervised scheme where labeled data is not required. A performance comparison with benchmark methods using several synthetic and field examples shows that the proposed method outperforms the traditional methods.
- North America > United States (0.28)
- Asia (0.28)
Submarine cable positioning using residual convolutional neural network based on magnetic features
Liu, Yutao (Chinese Academy of Sciences) | Wu, Yuquan (Chinese Academy of Sciences) | Huang, Liang (Zhejiang University) | Yang, Lei (Zhejiang Institute of Marine Geology Survey) | Kuang, Jianxun (Zhejiang Qiming Offshore Power Co., Ltd) | Yu, Wenjie (Zhejiang Qiming Offshore Power Co., Ltd) | Wang, Jianqiang (Zhejiang Institute of Hydrogeology and Engineering Geology) | Xu, Zhe (Zhejiang Engineering Survey and Design Institute Group Co., Ltd) | Li, Gang (Zhejiang University, Zhejiang University)
Accurate positioning is important for improving the efficiency of repairing submarine cables and reducing the related repairing cost. The magnetic anomaly produced by a submarine cable can be used to estimate its vertical and horizontal positions. A novel approach using magnetic data for estimating the position of submarine cables based on the 1-D residual convolutional neural network (RCNN) is investigated. Infinitely long ferromagnetic cylinder models with different parameters are used to generate datasets for the model training and testing. Tests on noisy synthetic datasets show that the developed 1-D RCNN method can capture detailed features related to the magnetic source position information, which are more accurate than the conventional Euler method in estimating the position of submarine cables. The developed 1-D RCNN method has also been successfully applied to processing field data. Furthermore, the processing workflow of our 1-D RCNN method is less noise sensitive compared with the conventional Euler method. The proposed 1-D RCNN method and its workflow open a new window for estimating the position of submarine cables using magnetic data.
Rajeev Ranjan Sinha is a product analyst at SLB for DELFI ProdOps, a scalable industry-proven production operations platform, based out of Houston. He graduated from IIT(ISM) Dhanbad with a bachelor’s degree in petroleum engineering. Sinha started his career in 2013 as a reservoir engineer based out of India. During the initial phase of his career, he provided training, software support, and consulting to oil and gas operators in South Asia in well, network, and reservoir modeling and simulation software products and worked on multiple field development planning projects. Since then, he gained expertise in digital oilfield technologies, production operations and optimization, artificial lift surveillance, pump health and prognostics, sand management, and digitalization of field equipment systems. He has judged several student paper contests and case studies and is currently serving as the vice-treasurer of the SPE-GCS Completions & Production Study Group. Sinha has authored 5 SPE publications on his topics of interests.
Aligned with the industry's commitment to engage young minds in the energy sector, the International Petroleum Technology Conference (IPTC) Education Week emerges as an event that surpasses conventional expectations, leaving its mark on expanding knowledge and preparing university students for the workforce. The IPTC Education Week is a collaborative effort between four international societies--the American Association of Petroleum Geologists (AAPG), the European Association of Geoscientists and Engineers (EAGE), the Society of Exploration Geophysicists (SEG), and the Society of Petroleum Engineers (SPE)--stands out as a unique opportunity. Each year, the multidisciplinary committee of these societies selects up to 100 students in sciences, geosciences, and engineering from institutions worldwide. This year's event took place in Dharan, Saudi Arabia, and over several days, selected students immersed themselves in an enriching and distinctive experience, extending beyond the horizons of the academic environment. This program prepares future professionals and leaders for the numerous challenges and opportunities related to the future of energy.
Embracing a mission of connecting the world of applied geophysics,the Society of Exploration Geophysicists (SEG) is a not-for-profit organization supporting more than 11,000 members from 126 countries. SEG's long-standing tradition of excellence in education, professional development, new business generation, and engagement cultivates a unique community platform that encourages collaboration and thought leadership for the advancement of geophysical science around the world. Headquartered in Houston, TX, SEG has a business office in Tulsa, OK and regional offices in Dubai, UAE and Beijing, China. SEG is a global society that fosters the expert and ethical practice of geophysics in the exploration and development of natural resources, in characterizing the near-surface, and in mitigating earth hazards by inspiring the geophysicists of today and tomorrow.
- North America > United States > Texas > Harris County > Houston (0.30)
- North America > United States > Oklahoma > Tulsa County > Tulsa (0.30)
- Asia > Middle East > UAE > Dubai Emirate > Dubai (0.30)
- Asia > China > Beijing > Beijing (0.30)
- Information Technology > Knowledge Management (0.82)
- Information Technology > Communications > Collaboration (0.82)