Improving the Understanding of Non-Matrix Components in a Brazilian Pre-Salt Carbonate Reservoir Using a Machine Learning Approach; #42610 (2025)

Joan M. Blanco, Luiza De Carvalho Mendes, João Ponte Souza, Jean Carlos Rangel Gavidia, Juan Villacreses, Guilherme Chinelatto, Mateus Basso, Alexandre Vidal

Search and Discovery.com

.... Once a transform is found and validated, through the quantification of the final prediction error, we produce a seismic volume whose Z value...

Coherence Attribute Applications on Seismic Data in Various Guises

Satinder Chopra, Kurt Marfurt

Unconventional Resources Technology Conference (URTEC)

... error filter-based (Bednar, 1998) and gradient structure tensor-based (Bakker, 2003). These algorithms vary in how they handle seismic character...

Application of Assisted History Matching Workflow to Shale Gas Well Using EDFM and Neural Network-Markov Chain Monte Carlo Algorithm

Sutthaporn Tripoppoom, Wei Yu, Kamy Sepehrnoori, Jijun Miao

Unconventional Resources Technology Conference (URTEC)

... by the networks, is validated for the NN prediction error. The objective of having calibration data set is to prevent the overtraining of NN. The training...

Surface Prediction using Rejection Sampling to Handle Non-linear Constraints

Petter Abrahamsen, Pål Dahle, Vera Louise Hauge, Ariel Almendral-Vazquez, Maria Vigsnes

CSPG Bulletin

...on for the prediction error. Simulated realizations using (4) are almost exact. There is a minor approximation that involves ignoring a correlation betwe...

The Added Value of Quantitative Seismic Integration in 3D Prediction of Petrophysical Properties and Facies. A Case History from Tunisian Ghadames Basin, Marini, Alfonso I.; Di Prete, Francesco, #90100 (2009)

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Identification of Volcanics and its Application for Reservoir Prediction of Bioclastic Dolostone: An Example From Bohai Bay Basin

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Integrating Probabilistic Neural Networks and Generalized Boosted Regression Modelling for Lithofacies Classifications and Formation Permeability Estimation

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Using Synthetic Seismic Models of Channelized Deepwater Slope Deposits to Inform Stratigraphic Interpretation and Reservoir Modeling

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Development of a Data-Driven Operational Design Tool for CO2 Sequestration in Shale Gas Reservoirs

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Seismic Reservoir Characterization of the Abadi Gas Field, Masela PSC Block, West Arafura Sea, Eastern Indonesia

Shinji Matsuura, Shin Saito, Yoshiro Ishii, Hiromi Honda, Ayato Kato, Takao Yagi

Indonesian Petroleum Association

..., and that prediction error will be reduced if the noise were reduced by re-processing. To detect the distribution and the source of the noise will be crucial...

Three-dimensional Seismic Inversion and Geostatistical Reservoir Modeling of the Rotliegend Gas Field

R. K. Shrestha, M. Boeckmann, S. Faruqi, M.-K. Wang

AAPG Special Volumes

... or sparse-spike deconvolution algorithm used a prediction error filter to predict the high-frequency amplitudes based on the pass-band frequency...

Seismic Lithology (AVO) Interpretation at the Badak and Nilam Fields in the Sanga Sanga Block, Kalimantan

William C. Ade, Ian T. McMahon, Wahyudin Suwarlan

Indonesian Petroleum Association

..., initial estimates were influenced by noise, so a spatial prediction error filter method was used. The benefit of this process is shown in Figure 16...

From WHP to BHP Using Machine Learning in Multi-Fractured Horizontal Wells of the Vaca Muerta Formation

Agustín Terminiello,Matías Nasca, Juan Filipich, Donald Mc Intyre, Pablo Crespo

Unconventional Resources Technology Conference (URTEC)

... complexity as required to minimize the prediction error. Among the models trained for this testing exercise there were linear regression models, decisions...

Use of Machine Learning to Predict Maximum Borehole Diameter for Multi-Stage Frac Completions

Murtadha J. AlTammar, Khaqan Khan, Rima T. Alfaraj, Rayan A. Alidi, Khalid M. Alruwaili

Unconventional Resources Technology Conference (URTEC)

... datasets showed good prediction accuracy with an average absolute percentage error of less than 6%. This proposed methodology for caliper prediction...

Intelligent Prediction of Shale Oil Fracturing Curves Based on A Sequence-to-Sequence Model

Leyi Zheng, Tianbo Liang, Yunjin Wang, Fujian Zhou, Junlin Wu, Bin Wang, Jiaming Zhang, Maoqin Yang, Gong Chen, Xingyuan Liang

Unconventional Resources Technology Conference (URTEC)

... prediction accuracy. Existing methods for predicting the wellhead pressure during hydraulic fracturing suffer from three primary limitations: error...

Machine Learning Prediction and the Impact of CO₂ Injection on S-Wave in 20 Years in the Legacy Well Field

Sharif Morshed, Shafiqul Alam Khan, Wu Hao

Unconventional Resources Technology Conference (URTEC)

... leaf nodes for training and validation data, as well as prediction error for both training and test data, are generated. A plot of total error vs...

Abstract: Uncertainty in Reservoir Parameter Estimation From Attributes; #90063 (2007)

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Abstract: Seismic Characterization of Statoils Leismer Heavy Oil Reservoir; #90172 (2014)

Rainer Tonn

Search and Discovery.com

... conversion is the evaluation of the uncertainty. Simulation results indicated that the depth prediction error to the base reservoir horizon in the densely...

The Identification of Volcanics and its Application for Reservoir Prediction of Bioclastic Dolostone: An Example From Bohai Bay Basin; #20240 (2014)

Jun Ming, Tongxing Xia, and Qingyun Bai

Search and Discovery.com

... of bioclastic dolostone. As a result, drilling of the bioclastic dolostone reservoir has resulted in two dry holes due to the reservoir prediction error...

Real Time Torque and Drag Analysis by Combining of Physical Model and Machine Learning Method

Kankan Bai, Honghai Fan, Hongbao Zhang, Fei Zhou, Xingang Tao

Unconventional Resources Technology Conference (URTEC)

...) and a horizontal well and the performance is compared with physical model and machine learning model respectively. It’s shown that the prediction error...

Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs

Nguyen T. Le, Roman J. Shor, Zhuoheng Chen

Unconventional Resources Technology Conference (URTEC)

... for multi-step ahead prediction, but the accumulation of error makes it more and more unstable as more and more estimated values of the target...

Chapter 13: Linking Cognitive Science and Disciplinary Geoscience Practice: The Importance of the Conceptual Model

Thomas F. Shipley, Basil Tikoff

AAPG Special Volumes

...-section prediction error is reporting the perspective shape of the 3-D solid at the cut location (Cohen and Hegarty, 2014). Students often misunderstand...

A Comparative Analysis of Machine Learning Techniques for Geothermal Wells Drilling Rate of Penetration (ROP) Prediction

Taha Yehia, Moamen Gasser, Hossam Ebaid, Nathan Meehan, Esuru Rita Okoroafor

Unconventional Resources Technology Conference (URTEC)

... (Vapnik, 2000). Definitely, following a robust ML workflow contributes to URTeC: 4044244 5 minimizing the prediction error of the ML models...

Research of accurate depth interpretation method for thin sand body in offshore reservoir and its application in A oilfield, Bohai Bay Basin

Li Wenbin, Hebing Tang, Xuetong Liu, Yichuan Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... guaranteed the deployment and implementation of more than 20 new wells with an average depth prediction error smaller than 2m. Our method is widely...

Spatio-Temporal Models for Big Data and Applications on Unconventional Production Evaluation

M. E. Wigwe*, E. S. Bougre, M. C. Watson, A. Giussani

Unconventional Resources Technology Conference (URTEC)

... apparent, depending on the position of the plot visa-vis the 45° diagonal line. The mean squared prediction error (MSPE) or its square root version (RMSPE...