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The AAPG/Datapages Combined Publications Database
Showing 129 Results. Searched 195,405 documents.
Convolution model theory-based intelligent AVO inversion method for VTI media
Yuhang Sun, Yang Liu, Hongli Dong
International Meeting for Applied Geoscience and Energy (IMAGE)
... based on Bayes theorem: Applied Geophysics, 8, 293–302, doi: https:// doi.org/10.1007/s11770-010-0306-0. Rüger, A., 1996, Reflection coefficients...
2023
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
Geological and Bioregional Assessments: Assessing Direct and Indirect Impacts Using Causal Networks
Luk J. M. Peeters, Kate Holland, Cameron R. Huddlestone-Holmes
Australian Petroleum Production & Exploration Association (APPEA) Journal
... using Bayes law or through Monte Carlo techniques. Bayesian networks combine a causal network with formal assessment of probabilities (Chen and Pollino...
2021
Uncertainty, Subjectivity and Bias, #120048 (2012)
Andrew Curtis, Matthew Walker
Search and Discovery.com
..., representing the decision point in a usual committee of experts. Figure 3. Top: Application of Bayes Rule to combine prior probabilities (e.g....
2012
Faunal Succession of Norian (Late Triassic) Level-Bottom Benthos in the Lombardian Basin: Implications for the Timing, Rate, and Nature of the Early Mesozoic Marine Revolution
Lydia S. Tackett, David J. Bottjer
PALAIOS
... if the favored models tend to support more change points or not. The Bayes factor for the more simplistic BIC model highly supported the top model over...
2012
A Novel Probabilistic Approach for GOR Forecast in UnconventionalOil Reservoirs
Yuewei Pan, Guoxin Li, Jianhua Qin, Jing Zhang, Lichi Deng, Ran Bi
Unconventional Resources Technology Conference (URTEC)
... with the Markov Chain Monte Carlo (MCMC) for better uncertainty quantification. Probabilistic approaches based upon Bayes’ theorem have been developed...
2021
Integrating Model Uncertainties in Probabilistic Decline Curve Analysis for Unconventional Oil Production Forecasting
Aojie Hong, Reidar B. Bratvold, Larry W. Lake, Leopoldo M. Ruiz Maraggi
Unconventional Resources Technology Conference (URTEC)
... used to weight the model forecast. Bayes’ theorem is used to assess the model probabilities for given data. Multiple samples of the model parameter...
2018
A Bayesian Framework for Addressing the Uncertainty in Production Forecasts of Tight Oil Reservoirs Using a Physics-Based Two-Phase Flow Model
Leopoldo M. Ruiz Maraggi, Larry W. Lake, Mark P. Walsh
Unconventional Resources Technology Conference (URTEC)
... psi, respectively. Bayesian Inference Bayesian inference uses probability to model uncertainty and variation. It uses Bayes’ theorem to update and esti...
2020
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
... five-fold CV (bottom) 6 URTEC-208394-MS Automatic searching methods that are commonly used include grid search, random search, and Bayes search...
2021
ON DRILLING FREQUENCY AND MANLY'S ALPHA: TOWARDS A NULL MODEL FOR PREDATOR PREFERENCE IN PALEOECOLOGY
JANSEN A. SMITH, JOHN C. HANDLEY, GREGORY P. DIETL
PALAIOS
... À Á 1 P ^Bayes . m a À Á 1 P ^Bayes , m a Pref. Group i 5 150 120 2 23 1 1 1 1 16 2 1 0 0 1 0 10 0 0 0 0 7 324 260 5 72 3 3 4 4 73 16 15 1 1 30...
2018
Uncertainty Analysis in Reservoir Characterization and Management: How Much Should We Know About What We Don't Know?
Y. Zee Ma
AAPG Special Volumes
... of infrequent data (Gillies, 2000; Ma, 2009b). Others think that the Bayes belief network cannot be fully believed because it is too subjective...
2011
A practical approach for applying Bayesian logic to determine the probabilities of subsurface scenarios: Example from an offshore oilfield
P. Craig Smalley, Christopher D. Walker, and Paul G. Belvedere
AAPG Bulletin
... a practical implementation of Bayes’ rule to update the probabilities of each scenario so that the probabilities are appropriately supported...
2018
Risk Analysis: Is it Really Worth the Effort?
Paul D. Newendorp
Southeast Asia Petroleum Exploration Society (SEAPEX)
... of terms such as risk analysis, expected value concept, conditional probability, EMV, decision trees, utility theory, Monte Carlo simulation, Bayes...
1978
Incertidumbre y Valor de Información en Proyectos Exploratorios [PAPER IN SPANISH] Uncertainty and Value of the Information in Exploratory Projects
Rober Yibirin, Juan F. Arminio
Asociación Colombiana de Geólogos y Geofisicos del Petróleo (ACGGP)
...Incertidumbre y Valor de Información en Proyectos Exploratorios [PAPER IN SPANISH] Uncertainty and Value of the Information in Exploratory Projects...
2009
Estimation of reservoir properties using a prestack seismic probabilistic inversion in gas-bearing tight sandstone reservoirs
Yongjian Zeng, Zhaoyun Zong, Kun Li
International Meeting for Applied Geoscience and Energy (IMAGE)
... on Bayes' theorem. Consequently, the inversion objective functional is obtained as follows: T 1 Ok m d d G H X, m, t m C1 d...
2023
Fuzzy Partitioning Systems for Electrofacies Classification: A Case Study from the Maracaibo Basin
J. J. Finol,, Y. K. Guo, X. D. Jing
Journal of Petroleum Geology
... to be known. This classification criterion is known as Bayes' rule of minimum error (Webb, 1999). Discriminant methods based on the Bayesian decision rule...
2001
Counterfactual uncertainty for high dimensional tabular dataset
Prithwijit Chowdhury, Ahmad Mustafa, Mohit Prabhushankar, Ghassan AlRegib
International Meeting for Applied Geoscience and Energy (IMAGE)
... to select our classifier models to carry out our analysis upon. We have used a Logistic Regresssion model, a Gaussian Naive Bayes, a Random Forest...
2023
Geostatistical and Flow Modeling of Intrareservoir Mudstones
Christopher D. White
Special Publications of SEPM
... is the fraction belonging to family i. The family fractions and parameters were estimated using a method based on Bayes' rule (Fig. 4A-D; White and Willis, 2000...
2004
Geostatistics and Stochastic Modeling: Bridging into the 21st Century
T. C. Coburn, J. M. Yarus, R. L. Chambers
AAPG Special Volumes
... developments have involved various flavors of stochastic simulation, the Markov chain Monte Carlo (MCMC), and the empirical Bayes modeling techniques...
2006
Distance Metric Based Multi-Attribute Seismic Facies Classification to Identify Sweet Spots within the Barnett shale: A Case Study from the Fort Worth Basin, TX
Atish Roy, Vikram Jayaram, Kurt Marfurt
Unconventional Resources Technology Conference (URTEC)
... of visualization these probabilities are projected as posterior probabilities back onto the 2D grid space, using Bayes theorem. Initially each target well...
2013
Kutei Basin: Feasibility Study of a Broadband Acquisition
Gilbert Del Molino, Fabri Ikhlas Gumulya, Dedy Sulistiyo Purnomo, Paolo Battini, Bonita Nurdiana Ersan, Francesca Brega, Ferdinando Rizzo, Giorgio Cavanna, Buia Michele
Indonesian Petroleum Association
... in the P-ImpedanceVp/Vs domain (figure 19). The PDFs allow, according to Bayes theorem rules, to derive the probability of facies occurrence for any...
2013
Application of Artificial Intelligence on Black Shale Lithofacies Prediction in Marcellus Shale, Appalachian Basin
Guochang Wang, Yiwen Ju, Timothy R. Carr, Chaofeng Li, Guojian Cheng
Unconventional Resources Technology Conference (URTEC)
... Bayes classifier based on maximum likelihood method, and fuzzy logic, one major problem is the predominant dependence on empirical risk...
2014
Bayesian geophysical inversion with Gaussian process machine learning and trans-D Markov chain Monte Carlo
Anandaroop Ray, David Myer
Petroleum Exploration Society of Australia (PESA)
... uncertainty) about the solution space (in our case, the earth’s subsurface conductivity). Bayes’ theorem bridges posterior and prior knowledge through...
2019
The Geochemistry and Microbial Ecology of Produced Waters from Three Different Unconventional Oil and Gas Regions
Kara Tinker, Daniel Lipus, Preom Sarkar, Djuna Gulliver
Unconventional Resources Technology Conference (URTEC)
... to classify the remaining sequences using a pre-trained Naive Bayes classifier trained on Silva 132 99% OTUs (Quast et al., 2012; Yilmaz et al., 2014...
2020
Applying Machine Learning Technologies in the Niobrara Formation, DJ Basin, to Quickly Produce an Integrated Structural and Stratigraphic Seismic Classification Volume Calibrated to Wells
Carolan Laudon, Jie Qi, Yin-Kai Wang
Unconventional Resources Technology Conference (URTEC)
..., and the Bayes factor, which shows the evidence of a statistical relationship between variables by giving a ratio of the likelihood of the data under...
2022