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...

A method of relative impedance holography-inversion based on reflection coefficient inversion

Jiangfeng Zheng, Jialin Sun, Zongyu Zhen, Shaoxuan Li

International Meeting for Applied Geoscience and Energy (IMAGE)

...) 𝑤 Where r(t, f) is the time-frequency spectrum of r(t), 𝑡 𝑤 is half-length of the time window. Assuming a convolutional seismogram and known wavelet...

Prediction of porosity in CO2 sequestration tight reservoirs based on multi-source and multi-scale data fusion

Ping Lu, Peixue Jiang, Ruina Xu, Huaqing Xue, Haojie Li, Lei Yu, Jiashu Han

International Meeting for Applied Geoscience and Energy (IMAGE)

... it difficult for the reservoir porosity model to simultaneously consider prediction accuracy and generalization performance. Therefore, this study focuses...

Prestack Seismic Data Inversion for Shale Gas Reservoir Characterization in China

Gang Yu, Yusheng Zhang, Ximing Wang, Xing Liang, Uwe Strecker, Maggie Smith

Unconventional Resources Technology Conference (URTEC)

...) the model is parallel vertical cracks (Thomsen, 1988). P waves travel with different velocities depending on their travel path with respect...

Understanding the Seismic Wavelet; Steven G. Henry; Search and Discovery Article #40028 (2001)

Search and Discovery.com

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)

... is happening downhole during drilling. This model can operate on both categories of data. For the real-time scenario, the AI model (Escobar et al. 2022...

Correlating Versus Inverting Vibroseis Records: Recovering What You Put into the Ground; #41577 (2015)

Glen Larsen, Paul Hewitt, Art Siewert

Search and Discovery.com

...) based on work of Allen et al. (1998). In effect, spiking the trace reduces it to a phase only operator. The usual vibroseis convolutional model is: x...

Prestack Seismic Data Inversion for Shale Gas Reservoir Characterization in China; #41829 (2016)

Gang Yu, Yusheng Zhang, Uwe Strecker, Maggie Smith

Search and Discovery.com

... of Horizontal Transverse Isotropy (HTI) the model is parallel vertical cracks (Thomsen, 1988). P waves travel with different velocities depending...

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...

Bayesian RockAVO: Direct petrophysical inversion with hierarchical conditional GANs

Miguel Corrales, Muhammad Izzatullah, Matteo Ravasi, Hussein Hoteit

International Meeting for Applied Geoscience and Energy (IMAGE)

... distribution, HiCond-GAN needs to be trained independently for each petrophysical model, thus increasing the computational cost and time in constructing...

Shaking up the Earth: The AI revolution in seismic interpretation

Ryan Williams

GEO ExPro Magazine

... teams to accurately interpret more seismic data in less time and often, with fewer resources. No longer feared as a black-box solution to replace...

Revisiting Brown Fields: A lookback on unforeseen opportunities in a late life field

Hifzhul ‘Arif Ahmad Munif, Ismail Marzuki Gazali, Hairul Hafez Abu Bakar, Alfian Termizi, Wan Mohd Nazrullah Mohamed Zin, Nur Syakirah Muhammad Yusoff, Zainal Arifin Suwito, Chin Tee Ang

International Meeting for Applied Geoscience and Energy (IMAGE)

... a major challenge back then due to the mismatch between the results from the Dynamic Model versus the actual well result, leading to 2 wells being...

Multi-conditional seismic velocity synthesis using an autoregressive transformer network

Randy Harsuko, Shijun Cheng, Tariq Alkhalifah

International Meeting for Applied Geoscience and Energy (IMAGE)

... in a generative model. These stored velocity model distributions can be utilized to regularize inverse problems, like full waveform inversion. However, most...

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

Search and Discovery.com

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)

... required per logging point, rendering them impractical for real-time applications. To overcome this issue, we set the formation model as the inputs...

Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network (Progressive GAN);

Suihong Song, Tapan Mukerji, Jiagen Hou

Search and Discovery.com

...Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network...

Abstracts: The Reflectivity Response of Multiple Fractures and its Implications for Azimuthal AVO Inversion; #90173 (2015)

Olivia Collet, Benjamin Roure, Jon Downton

Search and Discovery.com

... studying various rock physics models in order to model the impact of multiple fractures on the elastic parameters of an isotropic medium. Then, we...

Rapid Play Evaluation through AI Interpretation

Jacob Smith, Peter Szafian

Australian Petroleum Production & Exploration Association (APPEA) Journal

... inputs to interpretation and model­ ling (Han and Cader 2020). These techniques provide highquality imaging of faults in a fraction of the time...

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...

Interpolated fast and computational-efficient multidimensional singular spectrum analysis (I-FMSSA) for compressive simultaneous-source data processing

Rongzhi Lin, Yi Guo, Fernanda Carozzi, Mauricio D. Sacchi

International Meeting for Applied Geoscience and Energy (IMAGE)

... of receivers recording the data stimulated by several sources fired at close and randomdistributed time intervals. Despite being a great idea from a source...

DASF: A high-performance and scalable framework for large seismic datasets

Julio C. Faracco, Otávio O. Napoli, João Seródio, Carlos A. Astudillo, Leandro A. Villas, Edson Borin, Alan Souza, Daniel Miranda, João Paulo Navarro

International Meeting for Applied Geoscience and Energy (IMAGE)

..., the attribute to be calculated, the ML model to be trained or the waiting time in the HPC system’s queues. Finally, once the system finishes...

Joint Identification of Lithology and Lithofacies in Core Images Based on Deep Learning

Han Wang, Feifei Gou, Hanqing Wang, Shengjuan Cai

Unconventional Resources Technology Conference (URTEC)

... the lithology identification model. Two lithofacies recognition models are trained for different lithology types. For a core image, the lithology is first...

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...

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)

... reduces the time required to process passive seismic data. INTRODUCTION Seismic event location processing requires the identification of phase arrivals...

Time-Lapse Petro-Elastic and Seismic Modeling to Evaluate Fracturing Efficiency in Low-Permeability Reservoirs

Masoud Alfi, Zhi Chai, Anshuman Pradhan, Travis Ramsay, Maria Barrufet, John Killough

Unconventional Resources Technology Conference (URTEC)

... inputs, normal incidence seismic traces are forward-modeled through the convolutional model shown in Eq. 10. A zero-phase Ricker wavelet with a central...