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)

... performs as en-echelon and horsetail spray, which represents the dextral strike-slip of Apsheron ridge. The hydrocarbon accumulations are fault...

Neural network assisted responses simulation and data correction of array laterolog in invaded formations

Yueyang Han, Lei Wang, Donghan Hao, Xiyong Yuan, Nan Wang, Zhen Yang, Jianwen Zhou, Liwei Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... correction method for array laterolog in invaded formations. First, a three layered cylindrically layered model, which takes into account borehole...

Subsurface hydrogen storage: A feasibility study

Dwaipayan Chakraborty, Subhashis Mallick, Mortezaa Dejam

International Meeting for Applied Geoscience and Energy (IMAGE)

... models. The original model before H2 replacement is in cyan, the model after replacement is in black and the inverted model is in red. (b) observed...

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...

A prior regularized 3D full-waveform inversion using 2D generative diffusion models

Fu Wang, Tariq Alkhalifah, Xinquan Huang

International Meeting for Applied Geoscience and Energy (IMAGE)

... in observation, this inverse problem is highly ill-posed, especially for recovering a 3D velocity model. To solve this problem, regularization is often...

Uncertainty quantification of single and multi-parameter full-waveform inversion through a variational autoencoder

Abdelrahman Elmeliegy, Mrinal Sen, Jennifer Harding, Hongkyu Yoon

International Meeting for Applied Geoscience and Energy (IMAGE)

.... The input to the network is seismic shot gathers and the output are samples (distribution) of model parameters. We then use these samples to estimate...

Diagenesis and pore pressure induced dim spots „ Advances on AVO analysis of high-impedance reservoirs

Antonio Pessoa, Mark Chapman, Giorgos Papageorgiou

International Meeting for Applied Geoscience and Energy (IMAGE)

... stress scenario. Pressure-dependent AVO Analysis Seismic and Well Data Interpretation To conduct this AVO analysis, we assume a convolutional model...

Machine learning and explainable AI for predicting missing well log data with uncertainty analysis: A case study in the Norwegian North Sea

Sushil Acharya, Karl Fabian

International Meeting for Applied Geoscience and Energy (IMAGE)

..., followed by PCR and PLSR. Linear regression provides a baseline model for predicting DTC logs. PCR and PLSR are utilized to explore the potential...

Artificial Intelligence (AI) Based Personnel Protective Equipment (PPE) Monitoring - Case Study in Rokan Drilling Operation

Freddy Frinly Rizki, Ade Anggi N S, Ari Sukma Negara

Indonesian Petroleum Association

... and in different light conditions. The next step was to use deep learning technology such as Yolov4 and train the model using the PPE datasets...

Deep Learning for Quantitative Hydraulic Fracture Profiling from Fiber Optic Measurements

Weichang Li, Han Lu, Yuchen Jin, Frode Hveding

Unconventional Resources Technology Conference (URTEC)

... to the synced pump data independently; and II) a convolutional LSTM (long short-term memory) sequence learning model maps time segments...

Earth Model Building in Real-Time with an Automated Machine Learning Framework - A Midland Basin Example

Altay Sansal, Muhlis Unaldi, Edward Tian, Gareth Taylor

Unconventional Resources Technology Conference (URTEC)

...Earth Model Building in Real-Time with an Automated Machine Learning Framework - A Midland Basin Example Altay Sansal, Muhlis Unaldi, Edward Tian...

Unlocking the Potential of Unlabeled Data in Building Deep Learning Model for Dynamometer Cards Classification

Ramdhan Wibawa, Rosyadi Rosyadi, Maulirany Nancy, Muhammad Awqi Gibran, Supriono Hariyadi

Indonesian Petroleum Association

... for building a Convolutional Neural Network (CNN) model using state of the art Self-Supervised Learning (SSL). The need to identify moretypes of failure has been...

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...

Predicting Coiled-Tubing Drilling Dynamics Using Transformers

Carlos Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen

Unconventional Resources Technology Conference (URTEC)

... tailored for CTD drilling time series data. This model leverages its ability to learn long-term dependencies and subtle patterns within the data...

Boosting Visualization of Image Logs in 3D Towards Automated Well-Centric Interpretation

Eya Ghamgui, Chandramani Shrivastava, Martin Carles, Josselin Kherroubi

Unconventional Resources Technology Conference (URTEC)

.... For example, using a lightweight deep learning model, the tool detects and visually highlights fracture features, while providing information...

Machine-Learning Driven Prediction of Geological Marker Signatures

Shashin Sharan, Kaustubh Shrivastava, Per Irgens, Tatjana Scherschel

Unconventional Resources Technology Conference (URTEC)

... to predict markers. The procedure involves three steps: data conditioning, feature extraction, and model training. Initially, log data is preprocessed...

Delineation of Gas Sands by Seismic Stratigraphy in the Pericocal Area, Orinoco Heavy Oil Belt, Venezuela: Section IV. Exploration Methods

J. Licheri, N. Parra

AAPG Special Volumes

... are interpreted in terms of geology and/or presence of fluids, according to the convolutional model. -- The parameters that allow changes in the seismic...

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

Search and Discovery.com

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

Search and Discovery.com

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...

Hydraulic Fracture Monitoring Using Distributed Acoustic Sensing: A Case Study Using Dip-in Fiber

Chaoyi Wang, Yuanyuan Ma, David Eaton, Kelly MacDougall, Carolyn Furlong

Unconventional Resources Technology Conference (URTEC)

... is used for event detection, based on 2D binary image classification and a convolutional neural network (CNN) using Keras (Chollet et al., 2015...

Enhancing Lithology Classification through a Deep Learning Framework

P. Zhang, T. Gao, R. Li

Unconventional Resources Technology Conference (URTEC)

..., more data typically improves model accuracy but also increases costs, this research optimizes the utility of existing and common logs. To leverage...

Sedimentary History of Upper Ordovician Geosynclinal Rocks, Girvan, Scotland

John f. Hubert

Journal of Sedimentary Research (SEPM)

... "convolutional balls"--(D) upper zone of horizontal lamination--(E) pelite (figs. 9, 10, 11). In order to avoid the genetic assumption of gravity-controlled...

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...

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...