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Showing 129 Results. Searched 195,452 documents.
Probabilistic seismic interpolation with the implicit prior of a deep denoiser
Matteo Ravasi
International Meeting for Applied Geoscience and Energy (IMAGE)
... algorithm capitalizes on the property of a poorly known statistical theorem stating that ‘a minimum mean squared error denoiser acting on signals corrupted...
2023
Risk Reduction for Effectively Increasing Drilling Efficiency in the Thin Reservoirs of the Three Forks of the Williston Basin. A Case Study Employing a Geostatistical Seismically Constrained Subsurface Geomodel
Inna Tsybulkina, Cesar Marin, Kevin Chesser, Shane Mogensen, Samuel D. Fluckiger
Unconventional Resources Technology Conference (URTEC)
... density functions (PDFs). Bayes’ theorem represents a tool for defining the conditional probability which allows combining various pdfs into a global...
2016
Averaging Predictions of Rate-Time Models Using Bayesian Leave-Future-Out Cross-Validation and the Bayesian Bootstrap in Probabilistic Unconventional Production Forecasting
Leopoldo M. Ruiz Maraggi, Larry W. Lake, Mark P. Walsh
Unconventional Resources Technology Conference (URTEC)
... of the production data, it applies Bayes’ theorem to compute a probability (weight) for each model based on the value of their maximum likelihood function...
2021
From Inversion Results to Reservoir Properties, #40869 (2012)
M. Kemper, N. Huntbatch
Search and Discovery.com
... • Statistical connectivity analysis • P90, P50, P10 Net-to-Gross • Probability of being inside a polygon 1. Bayesian Classification Bayes‟ Theorem...
2012
Probabilistic centroid moment tensor inversions using geologically constrained priors: Application to induced earthquakes in the Groningen gas field, the Netherlands
La Ode Marzujriban Masfara, Cornelis Weemstra, Thomas Cullison
International Meeting for Applied Geoscience and Energy (IMAGE)
... THEORY Bayesian inference is the process of using Bayes’ theorem to evaluate the probability of a hypothesis (or model) m given the observed data d...
2023
Decision Making through a Bayesian Network for a Pipeline in Design
Francois Ayello, Guanlan Liu, Jiana Zhang
Australian Petroleum Production & Exploration Association (APPEA) Journal
... and will determine a much more accurate corrosion rate. MRV methodology The MRV methodology is a corrosion assessment framework (model) based on the Bayes’ theorem...
2019
Evolution of E & P Risk Analysis (1960-2017), #42063 (2017).
Peter R. Rose
Search and Discovery.com
... for applying Bayes’ Theorem to evolving project values and decisions; F. The Development Sector began adopting many of the probabilistic and statistical...
2017
Using Bayesian Leave-One-Out and Leave-Future-Out Cross- Validation to Evaluate the Performance of Rate-Time Models to Forecast Production of Tight-Oil Wells
Leopoldo M. Ruiz Maraggi, Larry W. Lake, Mark P. Walsh
Unconventional Resources Technology Conference (URTEC)
...n inference uses Bayes’ theorem to update and estimate the probability distribution of a hypothesis as more evidence or data is available. In our cas...
2021
Comparison of three Bayesian methods for lithofluid facies prediction using elastic properties
Jingfeng Zhang, Kevin Wolf, Anar Yusifov, Matt Walker, Pedro Paramo, Jeffrey Winterbourne, Reetam Biswas, Atish Roy, Qiang Liu, Xingchao Liu
International Meeting for Applied Geoscience and Energy (IMAGE)
..., henceforth referred to as Simple Bayesian, employs Bayes’ theorem (Wolf et al., 2023): p(𝑳𝑭|𝑬) ∝ p(𝑬|𝑳𝑭) ∗ p(𝑳𝑭), (1) where p...
2023
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
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
What to expect when you are prospecting: How new information changes our estimate of the chance of success of a prospect
Frank J. Peel and John R. V. Brooks
AAPG Bulletin
... theory, although it is unclear where it was first formulated. Salkind (2010) noted that it is implicit to Bayes’ theorem (Bayes, 1763) and the theory...
2015
A practical guide to the use of success versus failure statistics in the estimation of prospect risk
Frank J. Peel, and John R. V. Brooks
AAPG Bulletin
..., Special Publications 2004, vol. 239, p. 15–27, doi:10.1144/GSL.SP.2004.239.01.02. Bayes, T., 1763, An essay toward solving a problem in the doctrine...
2016
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
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
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
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
How to Make Good Decisions Examples From Exploration
Bernhard W. Seubert
Indonesian Petroleum Association
... of drilling a dry well, which incurs a comparatively small “regret cost”. Bayes' Theorem Considered more broadly, the score table and the reasoning behind...
2014
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
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
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
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
Bayesian artificial intelligence for geologic prediction: Fracture case study, Horn River Basin
S. M Agar, W. Li, R. Goteti, D. Jobe, S. Zhang
CSPG Bulletin
.... The calculations within a BN are developed from Bayes Theorem (Bayes, 1763) and are well established and widely used (see Morgan, 1968; Pearl 1986, 1987, 1988...
2019