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...

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...

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...

Improved Latin hypercube sampling inversion method of effective reservoir parameter considering compaction trend

Xuan Zheng, Zhaoyun Zong, Kun Luo

International Meeting for Applied Geoscience and Energy (IMAGE)

... as (Bayes, 1763): P ( R) P (m | R) P ( R | m) =  p ( R ) P ( m | R ) (5) P ( R ) P ( m | R ) dR  where m and R represent the parameters...

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...

Abstract: Sampling Methods to Determine Optimal Models, Model Resolution and Model Choice in Earth Science Modelling Problems, by Kerry Gallagher, Soren Nielsen, Karl Charvin, John Stephenson, Malcolm Sambridge, and Chris Holmes; #90066 (2007)

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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)

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Almond Formation Lithostratigraphic Genetic Units, Greater Wamsutter Field, Southwest Wyoming: Phase III: From Iterative Geostatistical Approach to High-Grading Well Locations, by Natasha M. Rigg and Jeffrey M. Yarus, #50159 (2009).

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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...

Bayesian RockAVO: Direct petrophysical inversion with hierarchical conditional GANs

Miguel Corrales, Muhammad Izzatullah, Matteo Ravasi, Hussein Hoteit

International Meeting for Applied Geoscience and Energy (IMAGE)

... the trained HiCond-GAN’s generator. RockAVO and HiCond-GAN are combined through unnormalized Bayes’ theorem, which establishes the relationship between...

Traveltime tomography and efficient physics-informed Bayesian inversion

Tian Qiao, George Turkiyah, Gerard T. Schuster

International Meeting for Applied Geoscience and Energy (IMAGE)

... Page 2040 © 2022 Society of Exploration Geophysicists and the American Association of Petroleum Geologists (1) Efficient Physics+Bayes’ Inversion norm...

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...

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...

Kriging-based surrogate models for convergence acceleration of Markov chains: An example of magnetotellurics-dix joint inversion

Alejandro Quiaro, Mauricio D. Sacchi

International Meeting for Applied Geoscience and Energy (IMAGE)

... is based on Bayes theorem, which quantifies the probability of a model given an observation. INTRODUCTION The energy industry, specifically resource...

Nonlinear broadband seismic inversion for fluid mobility

Xuan Zheng, Zhaoyun Zong

International Meeting for Applied Geoscience and Energy (IMAGE)

... Where χ = ln The Bayesian formula can be expressed as (Bayes, 1763): P ( R ) P ( S RI | R ) P ( R | S RI ) = (17) ∫ P ( R ) P ( S RI | R ) dR P ( R) 2...

Integrating deep directional resistivity with machine learning for improved well placement in the Nikaitchuq Field, North Slope Alaska

Christopher McCullagh, Joshua Zuber

International Meeting for Applied Geoscience and Energy (IMAGE)

... are included, Naïve Bayes being the exception. Table 1: Classification accuracy of each ML model with different training datasets. Case Studies...

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...

The Value of CSEM Data in Exploration "Best of EAGE", #40885 (2012)

Arild Buland, Lars Ole Løseth, Andreas Becht, Malgven Roudot, Tage Røsten,

Search and Discovery.com

... additional information. The modified (posterior) probability for a geological scenario Si after risk modification is given by Bayes law as P ( Si | D...

Determination of Potential Yield and Volatile Hydrocarbons from Well Logs in Potential Source Rocks

J. L. Lin, H. A. Salisch

Southeast Asia Petroleum Exploration Society (SEAPEX)

...] were studied by means of cross-plots and correlation analysis. Bayes multi-group discriminant analysis was used to determine the rock categories...

Transdimensional Bayesian gravity inversion and uncertainty analysis for salt reconstruction

Xiaolong Wei, Jiajia Sun, Mrinal K. Sen

International Meeting for Applied Geoscience and Energy (IMAGE)

... of the Bayes’ rule (Bayes, 1763), the a posteriori probability density (PPD) of trans-dimensional MCMC (Green, 1995) is written as: Some recent works...

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...

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...

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...

Geophysical Uncertainty: Often Wrong, But Never in Doubt, by William L. Abriel, #40182 (2005).

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The Battle Against Bayesian Amnesia, #70069 (2009)

Patrick Leach

Search and Discovery.com

...%” Page 2 Bayes’s Law (translated into Oil Patch from the original statistical jargon) • You start with what’s in the ground; what...