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The AAPG/Datapages Combined Publications Database
Showing 129 Results. Searched 195,354 documents.
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
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
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: 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
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
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
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
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
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
Using Bayesian Belief Networks to Evaluate Continuous Gas Resources (Shale Gas, Tight Gas, and Coal Bed Methane): Tools to Calibrate the Expert and Exploit Knowledge; #40571 (2010)
Kurt J. Steffen
Search and Discovery.com
... p(Depth|Area,Width) Bayes’ theorem allows us to calculate p(Depth|Area,Width) using the Belief Network shown above. Therefore we can build a single...
2010
Abstract: Tradeoffs in 3D Seismic Acquisition Between Shallow and Deep Objectives or Value of 3D High Density (Infill) Seismic Survey to Improve Economic Results of CBM Wells from Cow Creek Unit, by N. J. House; #90092 (2009)
Search and Discovery.com
2009
A New Approach for Production Forecasting from Individual Layers in Multi-Layer Commingled Tight Gas Reservoirs
Katarina Van Der Haar (nee Kosten), Manouchehr Haghighi
Australian Petroleum Production & Exploration Association (APPEA) Journal
... will be used. It uses Bayes’ theorem (Eqn 2) to update and estimate the probability distribution of a parameter after data is observed (Paryani et al...
2022
Maximizing Recoverable Reserves in Tight Reservoirs Using Geostatistical Inversion From 3-D Seismic: A Powder River Basin Case Study
Haihong Wang, Howard J. Titchmarsh, Kevin Chesser, Jeff Zawila, Samuel Fluckiger, Gary Hughes, Preston, Kerr, Andrew Hennes, Michael Hofmann
Unconventional Resources Technology Conference (URTEC)
...’ theorem is a statistical tool used to manipulate conditional probabilities. Mathematically, Bayes’ theorem defines the relative weight given to prior...
2015
A Quantitative and Probabilistic AVO Approach for Better Characterizing a Complex Oil and Gas Field in the Kutei Basin, Indonesia
M. Cardamone, A. Santagostino, B. Tambunan
Indonesian Petroleum Association
.... simple parametrical distributions (e.g. Gaussian/Cauchy) ℘(I,G | Fk) are fit to each set. Bayes theorem is applied to derive the probability P(Fk | I...
2003
Improved carbonate reservoir characterization using formation density derived from prestack simultaneous inversion: A case study in West Kuwait
Rajesh Rajagopal, Alanood Al Otaibi, Mohamed Hafez A. Jaseem, Taiwen Chen, Bahrouh Bader Faisal
International Meeting for Applied Geoscience and Energy (IMAGE)
... facies, Bayes theorem simply states that the probability at a certain facies at a particular point on the cross plot, is the data density of points...
2023
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
Bayesian Probabilistic Analysis to Quantify Uncertainties in Hydraulic Fracture Geometry - Application to Laminations and their Impact on Fracture Height
Mohit Paryani, Ahmed Ouenes
Unconventional Resources Technology Conference (URTEC)
... inference to the deterministic frac design models, the design parameters are linked to the Bayes theorem by assuming the prior distribution...
2019
Integrated Fluid Analysis Technique to Improve Evaluation on Fluid Potential in Downthrown Structure Prospect (Paper P32)
T. A. Tiur Aldha, G. T. Gunawan Taslim
Geological Society of Malaysia (GSM)
... us to investigate the uncertainty in AVO predictions. By using Bayes’ theorem, probability maps were then produced for different potential pore fluids...
2012
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
Petroleum Reserves: A Proposal for Methodology and Classification
Jean M. Bourdaire, Ronald Pattinson
Indonesian Petroleum Association
... Bayes theorem applies to subjective probabilities. It explains why and how our information, i.e. our expertise, is filtered and summarized into our...
1985
New Joint Categorical/Continuous Simultaneous Inversion Technology (Paper C9)
M. Kemper
Geological Society of Malaysia (GSM)
... regularization. Bayes’ Theorem in this case can be written as: π(Z|Sreal) ≈ L(Sreal|Z) p(Z) [5] Where π is the posterior distribution, L the likelihood...
2012
An Ensemble-Based History Matching Approach for Reliable Production Forecasting from Shale Reservoirs
Usman Aslam, Rafel M. Bordas
Unconventional Resources Technology Conference (URTEC)
..., given the forward model and the history data, is calculated using Bayes’ theorem. The first step is to assign a prior probability distribution...
2020
Integrate instead of ignoring: Base rate neglect as a common fallacy of petroleum explorers
Alexei V. Milkov
AAPG Bulletin
... of tests, the geological POS of the next prospect is equal to the exploration success rate (base rate). This is in line with the Bayes’ theorem (e.g....
2017
Multivariate fracture intensity prediction: Application to Oil Mountain anticline, Wyoming
Jason A. McLennan, Patricia F. Allwardt, Peter H. Hennings, Helen E. Farrell
AAPG Bulletin
...., 2002, Short note: Naive Bayes classifiers and permanence of ratios: Center for Computational Geostatistics (CCG) Report 4, 12 p.Sanders, C., M...
2009
Multi-realization seismic data processing with deep variational preconditioners
Matteo Ravasi
International Meeting for Applied Geoscience and Energy (IMAGE)
... with the help of Bayes’ Theorem; the posterior distribution can be defined up to its normalizing constant as, p(x|d)α pε (d|x)px (x), where pε (d|x...
2023