REVISITED BAYESIAN SEQUENTIAL INDICATOR SIMULATION: USING A LOG-LINEAR POOLING APPROACH
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Date
2022
Authors
Madani, Nasser
Journal Title
Journal ISSN
Volume Title
Publisher
Mathematics
Abstract
It has been more than a decade since sequential indicator simulation was proposed to model
geological features. Due to its simplicity and easiness of implementation, the algorithm attracts the
practitioner’s attention and is rapidly becoming available through commercial software programs for
modeling mineral deposits, oil reservoirs, and groundwater resources. However, when the algorithm
only uses hard conditioning data, its inadequacy to model the long-range geological features has
always been a research debate in geostatistical contexts. To circumvent this difficulty, one or several
pieces of soft information can be introduced into the simulation process to assist in reproducing such
large-scale settings. An alternative format of Bayesian sequential indicator simulation is developed
in this work that integrates a log-linear pooling approach by using the aggregation of probabilities
that are reported by two sources of information, hard and soft data. The novelty of this revisited
Bayesian technique is that it allows the incorporation of several influences of hard and soft data
in the simulation process by assigning the weights to their probabilities. In this procedure, the
conditional probability of soft data can be directly estimated from hard conditioning data and then be
employed with its corresponding weight of influence to update the weighted conditional portability
that is simulated from the same hard conditioning and previously simulated data in a sequential
manner. To test the algorithm, a 2D synthetic case study is presented. The findings showed that
the resulting maps obtained from the proposed revisited Bayesian sequential indicator simulation
approach outperform other techniques in terms of reproduction of long-range geological features
while keeping its consistency with other expected local and global statistical measures.
Description
Keywords
Type of access: Open Access, Bayesian updating, sequential indicator simulation, kriging, probability aggregation
Citation
Madani, N. (2022). Revisited Bayesian Sequential Indicator Simulation: Using a Log-Linear Pooling Approach. Mathematics