Quantification of Conceptual and Parametric Uncertainties in Fractured Reservoir Models

Paul R. La Pointe, Aaron Fox

AAPG Special Volumes

... is repeated for the entire data or a subset of it. To develop a measure of the model prediction error, the model is used to predict the withheld data...

Toward a global model for correction of bottomhole temperature data: Progress and limitations

Tala Maria Aabø, and Christian Hermanrud

AAPG Bulletin

... temperature data to error estimates on the SFT prediction. Practical application of these methods is, however, made difficult by the requirement...

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...

Geometric mode decomposition method for diffraction separation

Peng Lin, Suping Peng, Yang Xiang, Chuangjian Li, Xiaoqin Cui

International Meeting for Applied Geoscience and Energy (IMAGE)

... exploits the slope differences between reflections and diffractions and estimates the dominant reflection slopes via a prediction-error filter...

Joint physics-based and data-driven time-lapse seismic inversion: Mitigating data scarcity

Yanhua Liu, Shihang Feng, Ilya Tsvankin, David Alumbaugh, Youzuo Lin

International Meeting for Applied Geoscience and Energy (IMAGE)

..., however, the prediction error increases with time. We developed a time-lapse inversion workflow that does not require pre-existing training data...

Deterministic and Statistical Wavelet Processing

Lee Lu

Southeast Asia Petroleum Exploration Society (SEAPEX)

... of its previous values. Such a prediction filter is usually designed by minimizing the L2 norm (See discussion in chapter III (e) of the error...

Managing Frac Hits in Vaca Muerta Oil Development: Insights from a Case Study, Statistical Analysis, and Mitigation Strategies

Juan Filipich, Adrian Oscar Rasgido, Lucia Lamberghini, Victor Hugo Ñañez

Unconventional Resources Technology Conference (URTEC)

... algorithms (XGBoost and CatBoost), which iteratively focused on reducing prediction error and improved an initial model. The model validation involved...

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...

AVO and Inversion Contribute to Makassar Exploration Efforts

William L. Soroka, Herry Andiarbowo, Anung Widodo

Indonesian Petroleum Association

... the inversion result was 1581 m and the actual depth at which a gas bearing sand was encountered was 1577 m. The prediction was in error by only 4 m...

A Statistical Approach to Assessing Depth Conversion Uncertainty on a Regional Dataset: Cooper-Eromanga Basin, Australia

David Kulikowski, Catherine Hochwald, Dennis Cooke, Khalid Amrouch

Petroleum Exploration Society of Australia (PESA)

... the best (lowest prediction error) method for their given data set. This can be replicated and applied to any region around the world with 3D seismic data...

Coherence Attribute Applications on Seismic Data in Various Guises

Satinder Chopra, Kurt Marfurt

Unconventional Resources Technology Conference (URTEC)

...-based (Marfurt et al., 1998), variance-based coherence (Pepper and Bejarano, 2005), eigenstructure-based (Gersztenkorn and Marfurt, 1999), prediction...

Meramec Velocity Systematics

Jing Fu, Carl Sondergeld, Chandra Rai

Unconventional Resources Technology Conference (URTEC)

... and predicted Vs suggesting that the Meramec velocity systematic can provide a reasonable Vs prediction. A composite log plot of the shear estimation error...

Decomposition of Publicly Reported Combined Hydrocarbon Streams Using Machine Learning in the Montney and Duvernay

K. N. Darnell, K. Crifasi, G. Stotts, D. Tsang, V. Lavoie, T. Cross, D. Niederhut, J.A. Ramey, K. Sathaye

Unconventional Resources Technology Conference (URTEC)

... score (MAPE), which divides the total absolute prediction error by the total actual production, we evaluate the error of the recombined gas model...

2D Seismic and Well Log Data Integration to Predict Pore Pressure Distribution in Brilian Field, Bintuni Basin

Refsi Dian Paparezzi, Warto Utomo, Muhammad Thariq Almuqtadir

Indonesian Petroleum Association

... 2011). where w0, w1, w2, and w4 are weights. This weight can be reduced by minimizing the mean-squared prediction error (Hampson, Schuelke and Quirein...

An Integrated Analytics and Machine Learning Solution for Predicting the Anisotropic Static Geomechanical Properties of the Tuscaloosa Marine Shale

Cristina Mariana Ruse, Jamal Ahmadov, Ning Liu, Mehdi Mokhtari

Unconventional Resources Technology Conference (URTEC)

... in both vertical and horizontal directions and generate accurate closure stress estimates. The low prediction error achieved for the minimum horizontal...

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...

AAPG/Datapages Discovery Series No. 7: Multidimensional Basin Modeling, Chapter 19: Uncertainty of Petroleum Generation Using Methods of Experimental Design and Response Surface Modeling: Application to the Gippsland Basin, Australia

Wendebourg, J.

AAPG Special Volumes

... of the regression model based on the prediction error sum of squares (PRESS) residuals (Myers and Montgomery, 1995). The latter is an important coefficient...

Fluid Prediction from 3-D Seismic Data in Deepwater Sandstone Reservoirs: Applications from Cocuite Gas Field, Veracruz Basin, Southeastern Mexico

Fouad, Khaled, Jennette, David C., Soto-Cuervo, Arturo

GCAGS Transactions

.... The stepwise regression technique was used to define the best combination of attributes with the lowest prediction error (Draper and Smith, 1966...

Early EUR Indicator for Permian Basin Unconventional Resources Based on Hourly Flowback Data

Xueying Xie, Shunhua Liu, Courtney Leiker

Unconventional Resources Technology Conference (URTEC)

... not found.) for the entire dataset and can serve as the mid case 1-year cumulative oil production prediction. Error! Reference source not found. also...

Industry Consortium Insights: Benchmarking Bottomhole Pressure Calculations in Tight Unconventionals

M. Carlsen, A. Proaño, V. Chavali, C. H. Whitson, M. M. Dahouk, S. Mydland, S. Liem, N. Longenbaugh, R. Sinha, J. Billings, D. Axelson, A. Lerza, B. Collins, N. Lightner, J. v. Dijken, I. Arguello, M. Watson

Unconventional Resources Technology Conference (URTEC)

...l data. Additionally, our analysis does not reveal a consistent relationship between fluid ratio and prediction error, cautioning agains...

Three-Dimensional Seismic Attributes Help Define Controls on Reservoir Development: Case Study from the Red River Formation, Williston Basin

R. A. Pearson, B. S. Hart

AAPG Special Volumes

... of seismic attributes. The average prediction error from exclusion testing increases with the addition of a third attribute indicating two...

Proxy Models for Fast Transfer of Static Uncertainty to Reservoir Performance Uncertainty

Jose Walter Vanegas, Luciane Cunha, Clayton V. Deutsch

AAPG Special Volumes

... of Chemicals and Fuels Engineering, University of Utah, Salt Lake City, Utah, 264 p.Vanegas, J. W., J. C. Cunha, and L. B. Cunha, 2006, Prediction...

Abstract: Data Mining in Identifying Carbonate Litho-Facies from Well Logs Based from Extreme Learning and Support Vector Machines, by Emad A. El-Sebakhy, Ognian Asparouhov, Abdulazeez Abdulraheem, Abdul-Aziz Al-Majed, Donghui Wu, and Kris Latinski; #90105 (2010)

Search and Discovery.com

Abstract: Real-time Bit Wear Prediction and Deployment Validation in Challenging Hard and Heterogeneous Sandstones using 3D Detailed and Simplified Physics-Based Progressive Wear Models; #91204 (2023)

Guodong (David) Zhan, William B. Contreras Otalvora, Xu Huang, Reed Spencer, John Bomidi

Search and Discovery.com

... force model with the least training error and the least number of model fitting parameters is selected by the ensemble for performance prediction and bit...