Evaluation of Empirical Correlations and Time Series Models for the Prediction and Forecast of Unconventional Wells Production in Wolfcamp A Formation

Aimen Laalam, Houdaifa Khalifa, Habib Ouadi, Mouna Keltoum Benabid, Olusegun Stanley Tomomewo, Mouad Al Krmagi

Unconventional Resources Technology Conference (URTEC)

.... Li et al. (2022) developed a hybrid production prediction model combining convolutional neural networks (CNN) and long short-term memory (LSTM...

Seismic image resolution enhancement with limited-well datasets using deep learning

Son Phan, Haibin Di, Wenyi Hu, Aria Abubakar

International Meeting for Applied Geoscience and Energy (IMAGE)

... seismic single-channel deconvolution via convolutional sparse coding model: IEEE Geoscience and Remote Sensing Letters, 17, no. 8, 1415–1419. Yuan...

Chapter 7: Advanced Reservoir Characterization Using 3D Seismic Data in Badger Basin, Bighorn Basin, Wyoming

John E. Buggenhagen

Montana Geological Society

... model can be created. This detailed model can then be used to help locate subtle anomalies associated with unconventional reservoirs...

The use of FWI in coal exploration

Mehdi Asgharzadeh, Maryam Bahri, Milovan Urosevic

Petroleum Exploration Society of Australia (PESA)

... of a 2D earth model that represents subsurface geology in Goonyella coal mine in Queensland, Australia. We generated elastic synthetic shot records...

An AI approach to using magnetic gradient tensor analysis for quick depth and property estimation

David A. Pratt, K. Blair McKenzie, Anthony S. White

Petroleum Exploration Society of Australia (PESA)

... into the expert system whereas, it is very difficult to understand how a trained neural net model relates to the underlying geology. The AI system...

Assessment of Micro-Fracture Density using Combined Interpretation of NMR Relaxometry and Electromagnetic Logs

Lu Chi, Marcus, Elliot, Zoya Heidari, Mark Everett

Unconventional Resources Technology Conference (URTEC)

... NMR analytical model for fracture-pore coupling to account for micro-fractures in the rock. This model was verified through NMR numerical simulations...

Seismic super resolution method for enhancing stratigraphic interpretation

Chengbo Li, Qingrong Zhu, Baishali Roy

International Meeting for Applied Geoscience and Energy (IMAGE)

... 𝒎 and employ the convolutional model to illustrate the method. Assuming the wavelet is stationary within a given interval, the seismic can...

Nonlinear time difference detection of seismic image based on image registration

Rongwei Xu, Huazhong Wang, Bo Feng, Chengliang Wu

International Meeting for Applied Geoscience and Energy (IMAGE)

... inversion starting model from wells with dynamic time warping and convolutional neural networks: Geophysics, 87, no. 2, R223–R230, doi: https://doi.org...

Machine assisted drillhole interpretation of iron ore resource evaluation holes in the Pilbara

Daniel Wedge, Owen Hartley, Andrew McMickan, Eun-Jung Holden, Thomas Green

Petroleum Exploration Society of Australia (PESA)

... each drillhole. A 3D geological model can be created by identifying corresponding stratigraphic boundaries within multiple drillholes. These models...

Geophysics in gold hydrogen exploration

Mengli Zhang, Yaoguo Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... and technological advances that can be reconfigured to support the hy- Figure 2: Illustration of geologic H 2 model including source rocks and reservoirs. The top...

Application of Machine Learning Methods to Assess Progressive Cavity Pumps (PCPs) Performance in Coal Seam Gas (CSG) Wells

Fahd Saghir, M. E. Gonzalez Perdomo, Peter Behrenbruch

Australian Petroleum Production & Exploration Association (APPEA) Journal

... of Convolutional Auto Encoders (CAE) and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) methodologies to characterise...

Robust Event Recognition in Real-Time Hydraulic Fracturing Data for Live Reporting and Analysis

Samid Hoda, Jessica Iriarte

Unconventional Resources Technology Conference (URTEC)

..., transparent (white box), and extremely performant model that easily accommodates operating constraints. In turn, this enables real-time reporting...

Nonuniform dispersed source arrays for broadband seismic acquisition

Joaqun A. Acedo, Mauricio D. Sacchi

International Meeting for Applied Geoscience and Energy (IMAGE)

...-DSA data via the convolutional model and a source operator that plays the role of the restriction operator in CS (Candes, 2008). The latter contains...

Fracture Diagnostics in Naturally Fractured Formations: An Efficient Geomechanical Microseismic Inversion Model

Meng Cao, Mukul M. Sharma

Unconventional Resources Technology Conference (URTEC)

...Fracture Diagnostics in Naturally Fractured Formations: An Efficient Geomechanical Microseismic Inversion Model Meng Cao, Mukul M. Sharma URTeC...

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)

... an encoder network with a supervised contrastive loss (Khosla et al., 2020). Effectively this means that the model is trained to learn to associate...

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...

Artificial Intelligence Integration for Optimal Reservoir Data Analysis and Pattern Recognition

Dr. Leon Hamilton, Dr. Marianne Rauch

Unconventional Resources Technology Conference (URTEC)

.../Rho, Mu/Rho, poisson’s ratio, Pimpedance, S-impedance Building valid relationships between log and seismic attributes, building AI model Using AI...

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)

... learning (DL). The proposed method requires an ingenious data preconditioning scheme to provide a better sampled initial model for DL interpolation...

The Role of Forward Seismic Modeling: Outcrop Analogs of Deep-Water Architectures; #51679 (2020)

Jamie K. Pringle, David A. Stanbrook

Search and Discovery.com

... Olden gave guidance on GMA™ software. Robin Westerman and Leon Barens related the convolutional model used by GMA to the wider context of wavefield...

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

Search and Discovery.com

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...