... economic geology exploration geophysicist seg reservoir characterization american association interpretation seismic interpretation global change hydrocarbon exploration seismic image petroleum geology geological subdiscipline expanded abstract stratigraphic interpretation petroleum geologist...

... The success of deep learning algorithms is contingent on sufficient, accurate training data to learn accurate mathematical representations of data points and mirror the interpretation process. Unfortunately, scarce training sets are common in seismic interpretation and the algorithm performance...

... In this abstract, we show a novel machine learning-based diffusion model for seismic interpretation. In geophysics, reconstructing the subsurface structure from seismic data is an important inverse problem. Existing supervised machine learning (ML) solutions are to train a model to directly map...

... formation extraction abstract energy 10 efficiency seismic interpretation workflow The application of machine learning (ML) technology to seismic interpretation has greatly improved both workflow efficiencies and product quality. Advancements in speed, precision, and accuracy leads to valuable...

... computing interpretation american association energy 10 seismic interpretation Energy companies maintain numerous subsurface applications with local data stores. This can lead to upstream workflow inefficiency, data silos, and unnecessary cost. As the E&P industry continues its digital...

... and areal sampling density of subsurface data used to estimate volumes of Resources and Reserves Integrated seismic interpretation, an essential and unifying activity in assessing volumes and their uncertainty We present fundamental concepts of seismic interpretation in a unifying framework that highlights...

... In seismic interpretation, deep learning models frequently overfit to limited amount of annotated data. For this reason, well calibrated models and reliable uncertainty estimation are essential for the adoption of deep learning in modern interpretation workflows. However, existing approaches...

... geoscience interpretation mgom american association international figure society energy 10 seismic interpretation High resolution sequence stratigraphy of the Mexican Gulf of Mexico based on interpretation of well and seismic data Cian O Reilly*, Elisabeth Royce-Rogers (TGS) Summary Prolific...

... to the seismic interpretation, we should consider reducing the influence of multiples and enhancing the resolution of seismic data. On the basis of previous research, we proposed the technical combination consisting of the seismic special-purpose processing and 3D automatic interpretation in this paper...

... Constant improvements in seismic acquisition, processing, and conditioning technologies, allow geoscientists to obtain detailed seismic volumes. However, the useful and expensive information contained in these volumes is not always fully harnessed due to traditional seismic interpretation...

... machine learning iteration seismic interpretation iterative seismic facies classification recommendation Automated active learning for seismic facies classification Haibin Di*, Leigh Truelove, and Aria Abubakar, Schlumberger Summary While various machine learning algorithms, particularly supervised...

... exploration geophysicist representation society international conference seismic interpretation In seismic interpretation, pixel-level labels of various rock structures can be time-consuming and expensive to obtain. As a result, there oftentimes exists a non-trivial quantity of unlabeled data...

... geoscience interpreter contribution exploration geophysicist 10 prediction interpretation workflow artificial intelligence model building human expertise seismic interpretation earth model building mexico carbonate platform southern gulf Machine learning assisted seismic interpretation...

... Even though deep neural networks are incredibly successful in speeding up seismic interpretation, they are frequently met with skepticism. Specifically, the main critique of deep learning remains the lack of explainable predictions and their poor generalization to difficult textures...

...Seismic interpretation of structural features in the Kokako 3D seismic area, Taranaki Basin (New Zealand) Edimar Perico*, Petróleo Brasileiro S.A. and Dr. Heather Bedle, University of Oklahoma. Summary The Western Platform represents an important tectonic unit The basin experienced different...

... accuracy seismic interpretation inversion psdm data bohai bay depth-domain data Pre-stack depth migration (PSDM) has significant advantages in imaging complex structural areas. However, it cannot be avoided that the relative depth relationship between wells on the seismic section in time-domain...

... In the past decades, machine learning algorithms have been developed for accelerating the seismic interpretation process. For this purpose, benchmark availability for algorithm improvement in computational geophysics is imperative. However, in geosciences, the supply of open benchmark datasets...

... of the structures beneath the gas cloud areas on different migration sections are compared and analyzed through numerical models. It is recommended that seismic interpretation work can be carried out directly on the PSDM data in depth-domain to avoid the imaging problems of PSTM data and the structural trap...

... Session Start Time: 1:50 PM Presentation Time: 3:05 PM Location: 360C Presentation Type: Oral seismic data exploration geophysicist 10 deep structural framework upstream oil & gas water migration seg international exposition structural geology seismic interpretation structural...

.... Faleide, 2018, A case study on semiautomatic seismic interpretation of unconformities and faults in the southwestern Barents Sea: Interpretation, 6, no. 2, SD29 SD40, doi: httpsdoi.org/10.1190/INT-2017-0152.1. Chen, L., G. Papandreou, F. Schroff, H. Adam, and Google Inc. 2017, Rethinking atrous...