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Time Lapse Density Prediction For Reservoir Characterization Using Probabilistic Neural Networks At Postle Field Texas County Oklahoma
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Book Synopsis Time-lapse Density Prediction for Reservoir Characterization Using Probabilistic Neural Networks at Postle Field, Texas County, Oklahoma by : Andrea C. Vega Díaz
Download or read book Time-lapse Density Prediction for Reservoir Characterization Using Probabilistic Neural Networks at Postle Field, Texas County, Oklahoma written by Andrea C. Vega Díaz and published by . This book was released on 2012 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reservoir Characterization Using Seismic Attributes, Well Data, and Artificial Neural Networks by : Sylvain Toinet
Download or read book Reservoir Characterization Using Seismic Attributes, Well Data, and Artificial Neural Networks written by Sylvain Toinet and published by . This book was released on 2001 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Time-Lapse Vp/Vs Analysis for Reservoir Characterization, Rulison Field, Colorado by : Ramses G. Meza
Download or read book Time-Lapse Vp/Vs Analysis for Reservoir Characterization, Rulison Field, Colorado written by Ramses G. Meza and published by . This book was released on 2008 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applying artificial neural network technology in reservoir characterization studies by : Cem Okan Kılıç
Download or read book Applying artificial neural network technology in reservoir characterization studies written by Cem Okan Kılıç and published by . This book was released on 1998 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Application of Reservoir Characterization and Simulation to the Bartlesville Reservoir, Paradise Field, Payne County, Oklahoma by : Chenxia Xie
Download or read book The Application of Reservoir Characterization and Simulation to the Bartlesville Reservoir, Paradise Field, Payne County, Oklahoma written by Chenxia Xie and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimizing Geo-cellular Reservoir Modeling in a Braided River Incised Valley Fill by : Tiffany Dawn Jobe
Download or read book Optimizing Geo-cellular Reservoir Modeling in a Braided River Incised Valley Fill written by Tiffany Dawn Jobe and published by . This book was released on 2010 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reservoir characterization and optimization of Stockyard Field, Gaines County, West Texas by : Christopher Sembritzky
Download or read book Reservoir characterization and optimization of Stockyard Field, Gaines County, West Texas written by Christopher Sembritzky and published by . This book was released on 2001 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unconventional Reservoir Parameter Estimation by Seismic Inversion and Machine Learning of the Bakken Formation, North Dakota by : Jackson Ray Tomski
Download or read book Unconventional Reservoir Parameter Estimation by Seismic Inversion and Machine Learning of the Bakken Formation, North Dakota written by Jackson Ray Tomski and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research reported in this thesis focuses on the prediction of reservoir parameters and their uncertainties. The thesis comprises two studies. In the first part, I focus on quantitative and seismic interpretation problem, where I describe a workflow for estimation of porosity using the results from pre-stack seismic inversion. The second part focuses on the production problem, where I establish a relationship between completion parameters and production given a production dataset from the Bakken Formation. In the first study, I characterize the unconventional reservoir of the Bakken Formation, specifically within northwest North Dakota using 3D seismic and well log data. I employ seismic inversion followed by application of a Bayesian Neural Network to predict total porosity across the entire seismic volume given an estimated volume of P-impedance. The Bayesian Neural Network utilizes Markov Chain Monte Carlo via Langevin Dynamics in order to sample from the probability distribution and to estimate uncertainity. This method establishes a good correlation between estimated P-impedance from seismic inversion and total porosity from well data. By integrating these techniques, a better understanding of the parameters useful for reservoir characterization is possible given a degree of uncertainity thereby improving oil and gas exploration and risk assessment. In this second study, I make use of a production dataset of the Bakken Formation to identify production patterns in the field to establish a relationship between completion parameters and production. A random forest model is employed alongside the Bayesian Neural Network model to predict production given a set of predictive features found through a series of feature selection methods. I then aim to create various training and testing dataset scenarios through random sampling and clustering. I do this in order to reduce the sampling bias and ensure that the machine learning models are being trained and tested on data coming from similar geological regions with similar production rate values. With the integration of these techniques, a better understanding of the parameters useful for optimizing oil production is possible with a degree of uncertainity when using the Bayesian Neural Network
Book Synopsis Integrated Reservoir Characterization Using Nonparametric Regression and Multiscale Markov Random Fields by : Sang Heon Lee
Download or read book Integrated Reservoir Characterization Using Nonparametric Regression and Multiscale Markov Random Fields written by Sang Heon Lee and published by . This book was released on 2000 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition for Fractured Reservoir Characterization Using Subsurface Big Data by : Egbadon Ajibola Udegbe
Download or read book Pattern Recognition for Fractured Reservoir Characterization Using Subsurface Big Data written by Egbadon Ajibola Udegbe and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a significant increase in the quantity of data generated from monitoring technologies for subsurface operations such as permanent downhole sensors, as well as cross-hole and seismic surveys. Traditional models and techniques have proven inadequate for the purpose of extracting information from Big Data, in support of reservoir management and decision-making. In addition, the last decade has brought about increased exploration of unconventional reservoirs such as shale, due to more favorable economics resulting from advances in directional drilling and hydraulic fracturing. However, existing methods for describing induced and natural fracture characteristics in the subsurface are still evolving, and associated impacts on well performance are not completely understood. To attain optimal development of these resources, we require accurate characterization of fractures and reservoir characteristics from subsurface time-series and spatial data.The above challenges have the potential to be addressed by developing new Big Data analytic tools focused on identifying and characterizing complex subsurface features such as fractures, by exploiting pattern recognition and high-performance computing to uncover masked trends in large volumes of subsurface data. In support of this objective, real-time face detection techniques have been adapted to establish a pattern recognition methodology for feature extraction, statistical learning and probabilistic model evaluation. Under this framework, a set of easy-to-compute features based on Haar wavelets are extracted directly from the data, in order to serve as attributes for training a cascade of probabilistic tree-based ensemble classification models. As a use case for time-series data analytics, production data simulated from hydraulically fractured shale gas wells have been trained to identify candidates for re-stimulation treatment. Results demonstrate the viability of the proposed framework in recognizing favorable re-stimulation candidate wells using solely gas rate profiles, with improved accuracy over conventional tools such as type-curve matches. Secondly, the proposed methodology has been extended to help identify fractures in post-stack seismic data, which has been trained using raw seismic amplitude responses generated using a discontinuous Galerkin finite element seismic wave propagation model. Next, the approach has been validated using 3D post-stack seismic data from the Niobrara Shale interval within the Teapot Dome field in Wyoming. The applicability of the proposed framework has been demonstrated for identifying sub-seismic fractures, by considering the amplitude profile adjacent to interpreted fullbore microimage (FMI) well log data. The up-scaled spatial distribution of the predicted fractures shows agreement with existing geological studies and align with interpreted large-scale faults within the interval of interest.
Book Synopsis Seismic Driven Reservoir Characterization for Porosity Estimation by : Muhammad Naeem
Download or read book Seismic Driven Reservoir Characterization for Porosity Estimation written by Muhammad Naeem and published by . This book was released on 2015-04-11 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Probability Density Estimation with Neural Networks and Its Application to Blind Signal Processing by : Amir Sarajedini
Download or read book Probability Density Estimation with Neural Networks and Its Application to Blind Signal Processing written by Amir Sarajedini and published by . This book was released on 1998 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reservoir Characterization Using Nonparametric Regression Techniques by : Trond Mathisen
Download or read book Reservoir Characterization Using Nonparametric Regression Techniques written by Trond Mathisen and published by . This book was released on 2000 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Using Instantaneous Spectral Analysis as a Thin Bed Reservoir Characterization Tool by : Carlos Luis Cabarcas
Download or read book Using Instantaneous Spectral Analysis as a Thin Bed Reservoir Characterization Tool written by Carlos Luis Cabarcas and published by . This book was released on 2004 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reservoir Characterization Using Core, Well Log, and Seismic Data and Intelligent Software by : Rodolfo Soto Becerra
Download or read book Reservoir Characterization Using Core, Well Log, and Seismic Data and Intelligent Software written by Rodolfo Soto Becerra and published by . This book was released on 1998 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Strategies for Reservoir Characterization and Identification of Incremental Recovery Opportunities in Mature Reservoirs in Frio Fluvial-Deltaic Sandstones, South Texas: An Example from Rincon Field, Starr County. Topical Report by :
Download or read book Strategies for Reservoir Characterization and Identification of Incremental Recovery Opportunities in Mature Reservoirs in Frio Fluvial-Deltaic Sandstones, South Texas: An Example from Rincon Field, Starr County. Topical Report written by and published by . This book was released on 1995 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Cluster analysis in reservoir characterization by : Yasuhiro Muneta
Download or read book Cluster analysis in reservoir characterization written by Yasuhiro Muneta and published by . This book was released on 1994 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: