Probabilistic Modeling of Well Interference for Shale and Tight Development with Subsurface Uncertainty

Yuguang Chen, Ryan Burke, Tom Tran, Andrew Roark, Scott Hanson

Unconventional Resources Technology Conference (URTEC)

... realizations of model input parameters are considered for both petrophysical and geomechanical properties. Design of Experiments (DoE) are applied at each...

Using Machine Learning for Geosteering During In-Seam Drilling

Ruizhi Zhong, Ray L. Johnson Jr, Zhongwei Chen

Unconventional Resources Technology Conference (URTEC)

... effectively distinguish coals from noncoal formations during in-seam drilling. The developed machine learning model has the potential to identify coals...

Automation of passive seismic processing via machine learning and physics-informed methods

Ivan Lim Chen Ning, Laura Swafford, Mike Craven, Kevin Davies, Evan Earnest, Dean Thornton

International Meeting for Applied Geoscience and Energy (IMAGE)

... methods such as grid searching require considerable computational effort. They are also prone to errors like any other model-based method. Despite efforts...

Volumetric supervised contrastive learning for seismic semantic segmentation

Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib

International Meeting for Applied Geoscience and Energy (IMAGE)

... are based on assumptions from the domain of natural images that do not make use of seismic context. In order to incorporate this context within contrastive...

Viable Solutions to Overcome Weaknesses of Deep Learning Applications in Production Forecasting: A Comprehensive Review

Y. Kocoglu, S. Gorell

Unconventional Resources Technology Conference (URTEC)

... process the same time series data in multiple different ways and can be combined with other workflows or networks such as Convolutional Neural Network...

A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation

Vanessa Simoes, Atul Katole, Bhuvaneswari Sankaranarayanan, Tao Zhao, Aria Abubakar

Unconventional Resources Technology Conference (URTEC)

... wells, which serve as the basis for training an DL model for marker propagation. This model predicts major markers on the remaining wells, and a marker QC...

Pushing the limit of 5D interpolation using deep learning

Yangkang Chen, Hang Wang, Chao Li, Omar M. Saad

International Meeting for Applied Geoscience and Energy (IMAGE)

... prepare the initial model in the COP domain instead of the CMP domain is that, in a COP domain with certain offset values, the travel times for adjacent...

2023 Rocky Mountain Section Meeting; - Abstracts, #91206 (2023).

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A Novel System for Determining Flaring Efficiency Utilizing Optical Methods and Artificial Intelligence

Ángel E. Esparza, Joe Etheridge

Unconventional Resources Technology Conference (URTEC)

... to implement multiple layers within neural networks and conduct operations in isolation of user’s active participation. Convolutional Neural Networks (CNN...

Outcrop to Subsurface Reservoir Characterization of the Mississippian Sycamore/Meramec Play in the SCOOP Area, Arbuckle Mountains, Oklahoma, USA

Benmadi Milad, Roger Slatt

Unconventional Resources Technology Conference (URTEC)

... of Devonian-Mississippian strata. (C) Lithological model of the Mississippian Sycamore-Meramec strata in the SCOOP area. Figure 2. Location of data...

Counterfactual uncertainty for high dimensional tabular dataset

Prithwijit Chowdhury, Ahmad Mustafa, Mohit Prabhushankar, Ghassan AlRegib

International Meeting for Applied Geoscience and Energy (IMAGE)

... reveals valuable insights into model responses, enhancing decision-making, fairness analysis, and understanding of influencing factors. Our paper...

Application of Bayesian Optimized Deep Bi-LSTM Neural Networks for Production Forecasting of Gas Wells in Unconventional Shale Gas Reservoirs

Y. Kocoglu, S. Gorell, P. McElroy

Unconventional Resources Technology Conference (URTEC)

... in the future. Another well-known method for production forecasting is history matching a reservoir simulation model created for a real field...

Applying Conditional Generative Adversarial Networks for Seismic Data Reconstruction

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Abstract: Machine Learning Receiver Deghosting - Shallow Water OBN Data Example; #91204 (2023)

Rolf Baardman, Rob Hegge, Jewoo Yoo

Search and Discovery.com

...: The proposed supervised ML-method uses a convolutional neural network (CNN) with a two-channel input layer (P and Vz) and an output layer containing the up...

Geological Facies Prediction Using Computed Tomography in a Machine Learning and Deep Learning Environment

Uchenna Odi, Thomas Nguyen

Unconventional Resources Technology Conference (URTEC)

...-defined geological facie classifications. Once the machine understands the relationship between geological facies and CT scan physics, the resulting model...

Production Forecasting in Shale Reservoirs through Conventional DCA and Machine/Deep Learning Methods

Cenk Temizel, Celal Hakan Canbaz, Onder Saracoglu, Dike Putra, Ali Baser, Tomi Erfando, Shanker Krishna, Luigi Saputelli

Unconventional Resources Technology Conference (URTEC)

...-consuming process when one tries to estimate the multi-well pad performance in the field condition. In order to correctly model the flow of fluid...

Harnessing AI and Computer Vision for Efficient Geothermal Field Exploration and Prospect Evaluation

Moamen Gasser, Danny Rehg, Marcus Oesterberg, Nathan Meehan

Unconventional Resources Technology Conference (URTEC)

.... The model showed a great alliance with the experts’ prediction of the geothermal potential presence. This AI tool is an immensely powerful tool especially...

Probabilistic seismic interpolation with the implicit prior of a deep denoiser

Matteo Ravasi

International Meeting for Applied Geoscience and Energy (IMAGE)

... velocity model that mimics the Volve field (see Ravasi et al. (2022) for more details on the data creation process). Second, we consider the Volve field...

Neural network-based seismic data conditioning: Case study of engineering seismic survey data

Juan Lee, Yongchae Cho

International Meeting for Applied Geoscience and Energy (IMAGE)

... to generate training data of varying sizes. These data are then employed to construct an artificial neural network model. To address limitations...

Complex structure pattern and its control on reservoir distribution in the Apsheron ridge of South Caspian Basin, insights from integrated study of OBN seismic

Xiao Dengyi, Li Jianlin, Song Jiawen, Zhao Min, Li Xiaoliang, Chen Xin, Qi Qunli, Chen Shuangting, Li Qiang, Wang Bo, An Fuli, Wang Li, Liu Qiang, Cui Jinglin

International Meeting for Applied Geoscience and Energy (IMAGE)

... and indicate active tectonics event. Considering the strata deformation and fault throw from deep to shallow, it is believed that at these two stag es...

AAPG Rocky Mountain Section Annual Meeting; - Abstracts, #90301 (2017).

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Leveraging source-over-cable marine seismic field data for near offset reconstruction with deep learning

Owen Rohwer Huff, Jan Erik Lie, Andreas Kjelsrud Evensen, Aina Juell Bugge

International Meeting for Applied Geoscience and Energy (IMAGE)

... data collected with source-over-cable acquisition geometry as training data. First, a convolutional neural network (CNN) is trained to reconstruct...

Reservoir pressure monitoring via surface deformation inversion: integrating numerical modelling with evolutionary optimisation

Reza Abdollahi, Abbas Movassagh, Dane Kasperczyk, Manouchehr Haghighi

Australian Energy Producers Journal

... Pressure Based on Surface Displacement Using Image-To-Image Convolutional Neural Network Model. Frontiers in Earth Science 9, 712681. doi...

Active gamma-ray well logging pattern localization with reinforcement learning

Yuan Zi, Lei Fan, Xuqing Wu, Jiefu Chen, Shirui Wang, Zhu Han

International Meeting for Applied Geoscience and Energy (IMAGE)

... series target as a reference. The proposed model follows a top-down search procedure, which starts by investigating the whole welllog record...

Fine-Scale Lamination/Bedding, An Important Factor in Unconventional Reservoirs Hydrocarbon Productivity

Carlos Molinares-Blanco, D. Becerra-Rondon, H. Galvis-Portilla, D. Duarte

Unconventional Resources Technology Conference (URTEC)

...) and cherts (hard). The natural radioactivity of the rock was measured at every stratigraphic foot using a hand-held gamma-ray scintillometer model RS-120...