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)

... for frac monitoring, based on the analysis of both microseismic and low-frequency DAS signals. CandDiD-1 is one of the first projects in Canada...

Abstract: Hydrocarbon Generation and Expulsion Model for Upper Paleozoic Source Rocks in the Hangjinqi Area, Northern Ordos Basin, China;

Huijun Wang, Shuangfang Lu, Guiping Zhao

Search and Discovery.com

...Abstract: Hydrocarbon Generation and Expulsion Model for Upper Paleozoic Source Rocks in the Hangjinqi Area, Northern Ordos Basin, China; Huijun Wang...

Abstract: Missing Well-Log Data Prediction Using a Hybrid U-Net and LSTM Network Model; #91212 (2025)

Benard Sasu Oppong, Po Chen, En-Jui Lee, Wu-yu Liao

Search and Discovery.com

...Abstract: Missing Well-Log Data Prediction Using a Hybrid U-Net and LSTM Network Model; #91212 (2025) Benard Sasu Oppong, Po Chen, En-Jui Lee, Wu-yu...

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...

Seismic reservoir characterization of the Strawn Group, northern part of the Eastern Shelf, King County, North-Central Texas: Case study

Osareni C. Ogiesoba

International Meeting for Applied Geoscience and Energy (IMAGE)

...-frequency model. These reflectivities are then convolved with the wavelet to get the synthetic seismogram which is compared with the actual seismic...

Improving subsalt imaging using mode-converted waves and volumetric coherent noise attenuation in southern Gulf of Mexico

Riaz Alai, Nik Nur Halim C. Soh, M Shah B. Sulaiman, M. Iqbal Supardy, Kien Kok Lee, Sandeep Kumar, Syazwani Bt Suhairi, Christian Brinzer, Frederico Xavier de Melo, Hongyan Li, Iestyn Williams, Hugo Enrique Munoz Cuenca, Nolan Brand, Kate Glaccum, George Zhao, Saeeda Hydal, Khaled Abdelaziz, Emmi Sanchez Vargas

International Meeting for Applied Geoscience and Energy (IMAGE)

... originating from the base of salt bodies. All models are derived from convolutional-based (surface multiples), dip guided selective stacking...

Understanding Seismic Amplitudes, by Steve Henry, #40135 (2004).

Search and Discovery.com

Augmented Intelligence for Geoscience Data in Mature Basins

Jess B. Kozman and Lorena Pelgrin

GCAGS Transactions

... data, such as that encountered in mature basins with decades of archived well reports. We have deployed a pre-trained convolutional neural network...

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

John E. Buggenhagen

Montana Geological Society

... by This method was selected due to its ability to output a smoothly-varying velocity function. This low-frequency velocity model...

Convolutional Neural Networks for Semantic Segmentation of Micro-Pores in SEM Based Images of Shales

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Enabling grassroots digital transformation with a Python-Excel ML toolkit

Andrew C. Silver

International Meeting for Applied Geoscience and Energy (IMAGE)

... prior to doing it (see Figure 1; Pfeffer and Sutton, 2000; Silver, 2022). For knowledge workers who primarily serve as domain experts in geoscience...

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...

Automatic detection of DAS-recorded microseismic fracture reflections

Youfang Liu, Ivan Lim, Chen Ning, Kurt Nihei

International Meeting for Applied Geoscience and Energy (IMAGE)

...- and S-wave direct arrivals are identified, we transform the data from the T-X domain to the F-K domain. Reflections exhibit different velocity...

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...

AVA on communication cables: Principles and Examples from the North Sea

Ran Bachrach, Ali Sayed, Andrea Murineddu, Pilar Di Martino

International Meeting for Applied Geoscience and Energy (IMAGE)

... by conventional seismic acquisition. DAS sensor response has characteristic effects on the amplitude and frequency of the recorded wavefield (Sayed et al...

Convolution neural networks fault interpretation in the Brazilian presalt

Hugo Garcia, Edimar Perico, Ana Moliterno, Alexandre Kolisnyk, Michael Lowsby

International Meeting for Applied Geoscience and Energy (IMAGE)

... (homogeneous and stratified salt) that causes imaging shadow zones, loss of high frequency content, and high Artificial intelligence algorithms...

Using Deep Learning and Distributed Machine Learning Algorithms to Forecast Missing Well Log Data; #42234 (2018)

Chijioke Ejimuda, Emenike Ejimuda

Search and Discovery.com

... model. The model accuracy was very low (about 10%). However, currently we are using auto encoder and convolutional neural network ResNet deep...

Magnetotelluric inversion using supervised learning trained with random smooth geoelectric models

Lian Liu, Bo Yang, Yixian Xu, Dikun Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

... frequencies and observation stations, noise, and the model equivalence regarding its resolution (Backus & Gilbert 1967; Parker 1983). Geophysicists...

Strike-slip fault skeletonization based on deep learning cascade ant tracking method

Zhipeng Gui, Junhua Zhang, Rujun Wang, Yintao Zhang, Chong Sun, Mei Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Then, utilizing advantages of ant tracking, fault skeletonization also called as fault thinning is operated. Model test and real data application show: (1...

Label-defect tolerance ability of deep learning inversion networks and its applications

Yang Ping, Xu Hunqun, Liu Di, Tao Chunfeng, Wang Chengxiang, Yue Changqing

International Meeting for Applied Geoscience and Energy (IMAGE)

... inversion accuracy. Through model testing, we confirm that Deep Learning (DL) networks have the ability to tolerate labels’ defects, which we name...

Evaluation of AI-enhanced processing for automated passive seismic detection and location

Aaron Booterbaugh, Evgeny Naumov

International Meeting for Applied Geoscience and Energy (IMAGE)

... model and provide access to the rich datasets collected by both public arrays and Nanometrics’s private installations. CONVOLUTIONAL NEURAL NETWORK...

ABSTRACT: Deep forest cover classification of consecutive landsat imageries over Borneo

Azalea Kamellia Abdullah, Mohd Nadzri Md Reba, Nur Efarina Jali, Sikula Magupin, Diana Anthony

Geological Society of Malaysia (GSM)

... learning image classification algorithms such as Convolutional Neural Networks (CNN) attains higher accuracy mapping with low human interruption. Deep...

Artificial intelligence techniques to the interpretation of geophysical measurements

Desmond FitzGerald

Petroleum Exploration Society of Australia (PESA)

... SUMMARY Integration of geology and geophysics thinking requires a common earth model, that accommodates, with errors, all the features from...

Background noise suppression for DAS-VSP data using attention-based deep image prior

Yang Cui, Umair bin Waheed, Yangkang Chen

International Meeting for Applied Geoscience and Energy (IMAGE)

... classical (such as wavelet and curvelet) and dictionary-learning techniques, rely on distinguishing signal components in the transform domain, albeit...

Statistical Analysis of Estimated Ultimate Recovery: Comparing Machine Learning and Traditional DCA Methods in the Eagle Ford and Bakken

Palash Panja, Carlos Vega-Ortiz, Milind Deo, Brian McPherson, Rasoul Sorkhabi

Unconventional Resources Technology Conference (URTEC)

...) (Yan et al., 2021), the Temporal Convolutional Network (TCN) (Lea et al., 2016), and the transformer model (Vaswani et al., 2017). The efficacy of LSTMs...