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Page 527 of SPE Reservoir Evaluation & Engineering Vol. 2, Issue 6 [page]

<span title="">1999</span> <i title="Society of Petroleum Engineers"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_spe-reservoir-evaluation-engineering" style="color: black;">SPE Reservoir Evaluation &amp; Engineering </a> </i> &nbsp;
Kriging variance is also useful for stochastic simulation (e.g., via sequential Gaussian simulation’) in order to quantify the spatial uncertainty of the predictions.  ...  This is followed by the application of the method to model the porosity distribution across the field based on limited well data and extensive geological information regarding the distribution patterns  ... 
<span class="external-identifiers"> </span>
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Stochastic integration of seismic data and geologic scenarios: A West Africa submarine channel saga

Jef Caers, Sebastien Strebelle, Karen Payrazyan
<span title="">2003</span> <i title="Society of Exploration Geophysicists"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rowfysypenbyvifoij4asuq65y" style="color: black;">The Leading Edge</a> </i> &nbsp;
Multiple reservoir models were generated by stochastically reconnecting the disconnected channel geobodies following two alternative geologic scenarios.  ...  In a first step, we have used statistical pattern recognition to determine spatial variability of channel facies from 3D poststack amplitudes.  ...  The aim of stochastic simulation is then to generate multiple reservoir models each honoring the spatial continuity of the facies variogram model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1190/1.1564521">doi:10.1190/1.1564521</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6mijcnm7snb6lpyg6tcpk5syxe">fatcat:6mijcnm7snb6lpyg6tcpk5syxe</a> </span>
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Research Status of and Trends in 3D Geological Property Modeling Methods: A Review

Yuyang Liu, Xiaowei Zhang, Wei Guo, Lixia Kang, Jinliang Gao, Rongze Yu, Yuping Sun, Mao Pan
<span title="2022-06-02">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
The 3D geological property modeling includes two main components, grid model generation and property interpolation.  ...  For the interpolation methods aspect, most geological phenomena are nonstationary, to simulate various types of reservoirs; the main development trends are increasing geological constraints and reducing  ...  We express our sincere thanks for American Journal Expert (AJE) for their linguistic assistance. Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app12115648">doi:10.3390/app12115648</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gc55zlosnfcxha4pnw6vfngyaa">fatcat:gc55zlosnfcxha4pnw6vfngyaa</a> </span>
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Relationship between well pattern density and variation function of stochastic modelling and database establishment

Jinkai Wang, Kai Zhao, Zhaoxun Yan, Yuxiang Fu, Jun Xie
<span title="">2020</span> <i title="EDP Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/43w4njdiybhs5kr3okskkifg4i" style="color: black;">Oil &amp; Gas Science and Technology</a> </i> &nbsp;
For 3D geological modelling of oil and gas reservoirs, well pattern density is directly related to the number of samples involved in the calculation, which determines the variation function of stochastic  ...  establishes a variogram database of stochastic models for different well pattern densities.  ...  This work was supported by the National Natural Science Foundation of China (grant number 51504143; grant number 51674156).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2516/ogst/2020077">doi:10.2516/ogst/2020077</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/afw5p4tmhnh4powp52znvamlci">fatcat:afw5p4tmhnh4powp52znvamlci</a> </span>
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Development and application of 3D spatial modeling techniques for characterizing regional mechanical and hydraulic properties of rock masses

Katsuaki KOIKE
<span title="">2010</span> <i title="Japanese Committee for Rock Mechanics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jbrjnpcg4neh7eqqwy7ojss3ly" style="color: black;">International Journal of the JCRM</a> </i> &nbsp;
Accurate spatial modeling of geologic structures and properties are crucial for mechanical and hydraulic characterizations of rock mass.  ...  This report presents several methods that are grouped into two categories depending on the natures of geologic data: type I for the data originated from plural populations and type II for the data that  ...  In general the geologic data used for this modeling, which mostly originate from borehole investigations, well-logging, and core tests, are limited in the amount and spatial distributions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11187/ijjcrm.6.17">doi:10.11187/ijjcrm.6.17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kf2xano2r5cqzchw7qfv4pkzn4">fatcat:kf2xano2r5cqzchw7qfv4pkzn4</a> </span>
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Challenges in conditioning a stochastic geological model of a heterogeneous glacial aquifer to a comprehensive soft data set

J. Koch, X. He, K. H. Jensen, J. C. Refsgaard
<span title="2014-08-06">2014</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xjanl2qypjf63cwvjmqfpmzmra" style="color: black;">Hydrology and Earth System Sciences</a> </i> &nbsp;
This study integrates two distinct data sources into the stochastic modeling process that represent two extremes of the conditioning density spectrum: sparse borehole data and abundant SkyTEM data.  ...  The ensemble can be used in subsequent hydrogeological flow modeling to address the predictive uncertainty originating from the geological structure uncertainty.</p>  ...  This work is part of the NiCA (Nitrate Reduction in a Geologically Heterogeneous Catchment) project (www.nitrat.dk), which is funded by the Danish Council for Strategic Research. Edited by: M. Giudici  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/hess-18-2907-2014">doi:10.5194/hess-18-2907-2014</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ilsrm3vcsnc7jduyaqb3hmnbtu">fatcat:ilsrm3vcsnc7jduyaqb3hmnbtu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170706075605/http://www.hydrol-earth-syst-sci.net/18/2907/2014/hess-18-2907-2014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/34/12/34124207f2dd01c83d8e5aab6de16c7e0af2c1a8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/hess-18-2907-2014"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Challenges in conditioning a stochastic geological model of a heterogeneous glacial aquifer to a comprehensive soft dataset

J. Koch, X. He, K. H. Jensen, J. C. Refsgaard
<span title="2013-12-11">2013</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yoealyvdl5cppbhfojs7qfgu5i" style="color: black;">Hydrology and Earth System Sciences Discussions</a> </i> &nbsp;
This study integrates two distinct data sources into the stochastic modeling process that represent two extremes of the conditioning density spectrum: sparse borehole data and abundant SkyTEM data.  ...  The ensemble can be used in subsequent hydrogeological flow modeling to address the predictive uncertainty originating from the geological structure uncertainty.  ...  This work is part of the NiCA (Nitrate Reduction in a Geologically Heterogeneous Catchment) project (www.nitrat.dk), which is funded by the Danish Council for Strategic Research. Edited by: M. Giudici  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/hessd-10-15219-2013">doi:10.5194/hessd-10-15219-2013</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jxnbxbf7ifavbktbetus4coo44">fatcat:jxnbxbf7ifavbktbetus4coo44</a> </span>
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Multi-scale uncertainty quantification in geostatistical seismic inversion [article]

Leonardo Azevedo, Vasily Demyanov
<span title="2018-10-09">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Geostatistical seismic inversion is commonly used to infer the spatial distribution of the subsurface petro-elastic properties by perturbing the model parameter space through iterative stochastic sequential  ...  Within this setting, the large-scale geological (metaparameters) used to generate the petro-elastic realizations, such as the spatial correlation model and the global a priori distribution of the properties  ...  ACKNOWLEDGEMENTS The authors acknowledge Epistemy for the donation of academic licenses of Raven® and Schlumberger for the donation of Petrel®.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1810.03919v1">arXiv:1810.03919v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lk5nhwbrnfc6tnmqqwv7zc6gvi">fatcat:lk5nhwbrnfc6tnmqqwv7zc6gvi</a> </span>
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Stochastic simulation of the Fox kimberlitic diamond pipe, Ekati mine, Northwest Territories, Canada

L. Robles-Stefoni, R. Dimitrakopoulos
<span title="">2016</span> <i title="Academy of Science of South Africa"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/blcxcpdpvnahnf7bjinxj4m5uq" style="color: black;">Journal of the Southern African Institute of Mining and Metallurgy</a> </i> &nbsp;
Two MPS methods were tested for modelling the geology of a diamond pipe located at the Ekati mine, NT, Canada.  ...  Multiple-point simulation (MPS) methods have been developed over the last decade as a means of reproducing complex geological patterns while generating stochastic simulations.  ...  Thanks are in order to BHP Billiton Diamonds and, in particular, Darren Dyck, Barros Nicolau, and Peter Oshust for their support, collaboration, data from Ekati mine, and technical comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17159/2411-9717/2016/v116n2a10">doi:10.17159/2411-9717/2016/v116n2a10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q2dukvr5zrbzjl2ofqc577w6pu">fatcat:q2dukvr5zrbzjl2ofqc577w6pu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720163946/http://www.scielo.org.za/pdf/jsaimm/v116n2/13.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d0/d3/d0d31d849153b30aa7a1617363c55c2f59b31801.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17159/2411-9717/2016/v116n2a10"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Coupling geologically consistent geostatistical history matching with parameter uncertainty quantification [article]

Eduardo Barrela, Vasily Demyanov, Leonardo Azevedo
<span title="2018-10-11">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The resulting petrophysical model properties are conditioned to well data with respect to large-scale geological parameters such as spatial continuity patterns and their probability distribution functions  ...  The objective of this work is twofold: (i) to identify geological and fluid flow consistent areas of influence for geostatistical assimilation; and (ii) to infer large-scale geological uncertainty along  ...  Erasmus+ for supporting the MSc traineeship with Heriot-Watt University, Rock Flow Dynamics for providing the licenses for tNavigator as well as MathWorks and Schlumberger for the donation of academic  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1810.06642v1">arXiv:1810.06642v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4zi4oelmljcc5jxogcqr7r565m">fatcat:4zi4oelmljcc5jxogcqr7r565m</a> </span>
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Stochastic rock type modeling in a porphyry copper deposit and its application to copper grade evaluation

Hassan Talebi, Omid Asghari, Xavier Emery
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kfl5p7ytxra6vlm6rovoiwkmke" style="color: black;">Journal of Geochemical Exploration</a> </i> &nbsp;
Instead, stochastic models based on geostatistical simulation allow assessing the uncertainty in the spatial layout of the domains.  ...  These probabilities are then used for weighting the copper grade prediction associated with each domain so as to obtain the final grade model.  ...  The authors are also grateful to Sungun copper mine for providing the dataset used in this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.gexplo.2015.06.010">doi:10.1016/j.gexplo.2015.06.010</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/go4p4u6uffb7vaehbsegkofera">fatcat:go4p4u6uffb7vaehbsegkofera</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923031917/http://repositorio.uchile.cl/bitstream/handle/2250/135059/Stochastic-rock-type.pdf?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/54/06/54068a109519f69cb7aae70401aab93fe7b29255.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.gexplo.2015.06.010"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Page 2239 of Mathematical Reviews Vol. , Issue 83e [page]

<span title="">1983</span> <i title="American Mathematical Society"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_mathematical-reviews" style="color: black;">Mathematical Reviews </a> </i> &nbsp;
Ord, Time-series and spatial patterns in ecology (pp. 1-94); Peter J. Diggle, Statistical methods for spatial point patterns in ecology (pp. 95-150); R. M.  ...  Ludwig, A test of different quadrat variance methods for the analysis of spatial pattern (pp. 289-303); S. A. L. M. Kooijman, The description of point patterns (pp. 305-331); R.  ... 
<span class="external-identifiers"> </span>
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Page 85 of Geographical Analysis Vol. 21, Issue 1 [page]

<span title="">1989</span> <i title="John Wiley &amp; Sons, Inc."> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_geographical-analysis" style="color: black;">Geographical Analysis </a> </i> &nbsp;
There follows a discussion of some particular stochastic models, such as those for randomly located points.  ...  (The examples of mechanisms producing point patterns that are more regular than those of a two-dimensional Poisson process have been much quoted by later authors, as Matérn points out [p. 149] in his Postscript  ... 
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Hydrostratigraphic modelling using multiple-point statistics and airborne transient electromagnetic methods

Adrian A. S. Barfod, Julien Straubhaar, Anne-Sophie Høyer, Júlio Hoffimann, Anders V. Christiansen, Ingelise Møller, Jef Caers
<span title="2017-08-22">2017</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yoealyvdl5cppbhfojs7qfgu5i" style="color: black;">Hydrology and Earth System Sciences Discussions</a> </i> &nbsp;
Using Multiple Point Statistics (MPS) for stochastic hydrostratigraphic modelling provides a degree of flexibility that allows the incorporation of elaborate datasets and provides a framework for stochastic  ...  Creating increasingly realistic hydrological models involves the inclusion of additional geological and geophysical data in the hydrostratigraphic modelling procedure.  ...  The funding for HyGEM is provided by the Danish Council for Strategic Research. Edited by: Monica Riva Reviewed by: two anonymous referees  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/hess-2017-413">doi:10.5194/hess-2017-413</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bvmy27wlpfaybf7rhzbsgoxmra">fatcat:bvmy27wlpfaybf7rhzbsgoxmra</a> </span>
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Bayesian inversion of seismic attributes for geological facies using a Hidden Markov Model

Muhammad Atif Nawaz, Andrew Curtis
<span title="2016-11-02">2016</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m44dlrcxv5g5vltcbroqffdoqq" style="color: black;">Geophysical Journal International</a> </i> &nbsp;
Walker & Curtis (2014) developed a method for Bayesian inversion of two-dimensional spatial data using an exact sampling alternative to McMC which always draws independent samples of the target distribution  ...  We propose a more efficient method for Bayesian inversion of categorical variables, such as geological facies that requires no sampling at all.  ...  In a 2D-HMM, the geological facies are assumed to follow a geological continuity model reflecting the joint spatial distribution of geologically plausible facies patterns over a rectangular 2D In this  ... 
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