Welcome to the new Datapages Archives
Datapages has redesigned the Archives with new features. You can search from the home page or browse content from over 40 publishers and societies. Non-subscribers may now view abstracts on all items before purchasing full text. Please continue to send us your feedback at emailaddress.
AAPG Members: Your membership includes full access to the online archive of the AAPG Bulletin. Please login at Members Only. Access to full text from other collections requires a subscription or pay-per-view document purchase.
Welcome to the new Datapages Archives
Search Results > New Search > Revise Search
The AAPG/Datapages Combined Publications Database
Showing 129 Results. Searched 195,354 documents.
Abstract: The Probability Problems in the Prospect Appraisal
Hsu Yeong-Yaw
Geological Society of Malaysia (GSM)
... parameters are the subjective geological judgement of the analyst; however, by the Bayes' rule, the latest new objective information can...
1987
Probability Problems in Prospect Appraisal
Hsu Yeong-Yaw
Geological Society of Malaysia (GSM)
... geological judgement of the analysis; however, by the Bayes' rule, the latest new objective information can be incorporated into the original estimation...
1988
Evaluation of Machine Learning Methods for Automatic Facies Classification As a Tool for Determining Sandstone and Limestone Reservoir
Irvan Rahadian Putra, M. Irsyad Hibatullah, Christopher Salim, Firman Syaifuddin
Indonesian Petroleum Association
... objects based on its unique features. This specific machine learning model is a probabilistic model that follows the Bayes theorem, where the probability...
2019
Bayesian Updating of Toxic Leakage Scenarios
Ian Lerche
Environmental Geosciences (DEG)
... leakage events. Bayes, T. (1783). An essay towards solving a problem in the doctrine of chances. Phil Trans Roy Soc, 53, 370–418. One of the major...
2001
Ranking DHI attributes for effective prospect risk assessment applied to the Otway Basin, Australia
Sebastian Nixon, Tony Hallam, Andrew Constantine
Petroleum Exploration Society of Australia (PESA)
... in ranking drilling opportunities. We demonstrate how we apply our understanding of DHI statistics from the Otway Basin, using Bayes' theorem. Key...
2018
Abstract: A Newton-Raphson Iterative Scheme for Integration of Multiphase Production Data into Reservoir Model, by Z. Wu; #90911 (2000)
Search and Discovery.com
2000
ABSTRACT: Application of Novel Machine Learning Algorithms for Facies Classification; #90115 (2010)
Olivier Malinur and Cyril U. Edem
Search and Discovery.com
..., Support Vector Machine, C4.5 Classification Trees, Naïve Bayes, Random Forest and CN2 Rule inducer. We also introduced Hierarchical Cluster Analysis...
2010
Machine Learning Approach in Identifying Wellbore Integrity Issue from Drilling Reports in Mahandini Field
Ragil S. Wardana, Rio Afriyanto, Dian S. Nasution
Indonesian Petroleum Association
... with relatively small number of datasets. Naïve Bayes algorithm is a probabilistic classifier based on the Bayes’ theorem. The classifier calculates...
2019
Microseismic Without Dots Probabilistic Interpretation and Integration of Microseismic Surveys
Ulrich Zimmer
Unconventional Resources Technology Conference (URTEC)
... all information is represented by PDFs, Bayes theorem can be effectively used to integrate this information consistently. It also allows...
2017
Abstract: Geostatistical Simulation of Reservoir Heterogeneity in a Lower Mississippian Sandstone, Appalachian Basin, by M. E. Hohn and R. R. McDowell; #90987 (1993).
Search and Discovery.com
1993
Abstract: Estimating Shale Length Distributions from Outcrop Data, by Christopher D. White and Brian J. Willis; #90914(2000)
Search and Discovery.com
2000
ABSTRACT: Comparison of Multivariate Statistical Algorithms for Wireline Log Facies Classification, by Tang, Hong, Christopher D. White, M. Royhan Gani, Janok Bhattacharya; #90026 (2004)
Search and Discovery.com
2004
Abstract: Geostatistical Integration of Outcrop and Geophysical Data to Describe Diagenetic Heterogeneities for Flow Modeling, Frontier Formation, Wyoming, by Hong Tang; #90039 (2005)
Search and Discovery.com
2005
Abstract: A Novel Approach to Reservoir Characterization Using Seismic Inversion, Rock Physics and Bayesian Classification Scheme, by Nader C. Dutta; #90077 (2008)
Search and Discovery.com
2008
Rock Physics and Reservoir Inference Study from Cretaceous Sandstones from Espirito Santos Basin, Brazil, Loures, Luiz; Pereira, Edinei; Fernandes, Flávio; Felix, Luciana, #90100 (2009)
Search and Discovery.com
2009
ABSTRACT: Bayesian Inversion Technique to Identify Spatial Continuity in Rock Properties Using Level Set Methods. Real Case Study on Horn Mountain Field, Deepwater Gulf of Mexico, by Dadi, Sireesh K.; #90142 (2012)
Search and Discovery.com
2012
Abstract: Probabilistic Seismic Facies Estimation of a Mississippian Tripolitic Chert Reservoir through Generative Topographic Mapping, by Roy, Atish; Kwiatkowski, Tim J.; Marfurt, Kurt; #90163 (2013)
Search and Discovery.com
2013
ABSTRACT: A Review of Applications of Artificial Intelligence for Predictive Analysis in Petrophysics - Practical Example Using Symbolic Regression; #90115 (2010)
Olivier Malinur
Search and Discovery.com
... Bayes analysis coupled with the use of nomograms turns as extremely powerful in stochastic prediction. Some methods focus on retrieving underlying...
2010
Abstracts: Seismic Lithology Prediction A Montney Shale Gas Case Study; #90173 (2015)
John Nieto, Franck Delbecq, and Bogdan Batlai
Search and Discovery.com
... could be further enhanced by creating Lithocubes with the above classification. The technique used here was based on Bayes Theorem and combined...
2015
Abstract: Geologic Risking with Bayesian Methods: Fracture Case Study in an Unconventional Setting; #90319 (2018)
Susan M. Agar, Weichang Li, Rajesh Goteti, T. Dawn Jobe, Yan Zaretskiy, Shuo Zhang
Search and Discovery.com
... classes. Further nodes serve as “symptoms” of fractures and can be used for validation. The node states of the Bayes net can be defined by data...
2018
Quantifying Uncertainty in Original-Oil-In-Place Estimates from Volumetric and Material Balance Methods, by C. Ogele, D.A. McVay, and W.J. Lee; #90052 (2006)
Search and Discovery.com
2006
2008
Auto Recognition of Carbonate Sedimentary Facies Based on an Improved BP Neural Network
Search and Discovery.com
N/A
The Machine Learning's Classification Methods Comparison to Estimate Electrofacies Type, Lithology and Hydrocarbon Fluids from Geophysical Well Log Data
Dimas Andreas Panggabean, Jihan Hardiyanti Arief, Lucky Kriski Muhtar, MN Alamsyah
Indonesian Petroleum Association
... Classifier (NB) is a classification technique based on the Bayesian Theorem. Naïve Bayes Classifier assumes that all features in the classification...
2021
Abstract: Stabilizing Seismic Absorption Compensation; #90171 (2013)
Changjun Zhang
Search and Discovery.com
.... Statistical inversion theory is, commonly, based on Bayes's Theorem. Because in an inverse problem, we always have observed data d , p(m | d...
2013