English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Multiple-point statistics (MPS) has shown promise inrepresenting complicated subsurface structures. For a practicalthree-dimensional (3-D) application, however, one of the critical issues isthe difficulty in obtaining a credible 3-D training image. However,bidimensional (2-D) training images are often available because establishedworkflows exist to derive 2-D sections from scattered boreholes and/or othersamples. In this work, we propose a locality-based MPS approach toreconstruct 3-D geological models on the basis of such 2-D cross sections (3DRCS),making 3-D training images unnecessary. Only several localtraining subsections closer to the central uninformed node are used in theMPS simulation. The main advantages of this partitioned search strategy arethe high computational efficiency and a relaxation of the stationarityassumption. We embed this strategy into a standard MPS framework. Twoprobability aggregation formulas and their combinations are used to assemblethe probability density functions (PDFs) from different subsections.Moreover, a novel strategy is adopted to capture more stable PDFs, where thedistances between patterns and flexible neighborhoods are integrated onmultiple grids. A series of sensitivity analyses demonstrate thestability of the proposed approach. Several hydrogeological 3-D applicationexamples illustrate the applicability of the 3DRCS approach in reproducingcomplex geological features. The results, in comparison with previous MPSmethods, show better performance in portraying anisotropy characteristicsand in CPU cost.

Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections