Document Details
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Document Type |
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Article In Conference |
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Document Title |
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Characterization of subsurface heterogeneity: Integration of soft and hard information using multi-dimensional coupled Markov chain approach توصيف عدم التجانس في الطبقات تحت السطحية : تكامل المعلومات اللينة والصلبة باستخدام مدخل سلسلة ماركوف المزدوجة المتعددة الأبعاد |
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Document Language |
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English |
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Abstract |
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Characterization of subsurface heterogeneity: Integration of soft and hard information using multi-dimensional Coupled Markov chain approach
Eungyu Park1+, Amro Elfeki2*, and Michel Dekking3
1. Environmental Sciences Division, Oak Ridge National Laboratory, PO Box 2008, MS6036, Oak Ridge, TN 37831-6036, USA.
+ Contact: parke@ornl.gov
2. Section Hydrology and Ecology, Faculty of Civil Engineering and Geosciences, Delft University of Technology P.O. Box 5048, 2600 GA, Delft, The Netherlands
3. Section of Applied Probability, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
Abstract
Subsurface heterogeneity is a complex mixture of discrete structures characterized by more or less discontinuous boundaries (e.g., lithologies, faults) and random features that may be characterized by statistical models. The development of models capable of mathematically mimicking such complex variability has proven difficult. Conventional semivariogram-based geostatistical methods have difficulty incorporating geologic interpretations into models and are unable to describe non-stationary distributions and asymmetric juxtapositional tendencies. Transition probability-based indicator models have been proposed to address these problems. Carle and Fogg (1997) proposed a Markov chain model in conjunction with a conventional sequential indicator simulation algorithm. Elfeki and Dekking (2001) developed a two-dimensional coupled Markov chain model that uses a conditional simulation algorithm with explicit transitional conditioning probability equations. More recently, Park et al. (2002) extended this model to three-dimensional space and improved the algorithm to more readily utilize sparsely located hard data. Advantages of the coupled Markov chain approach include: (1) the procedure is simpler than conventional sequential indicator simulation because the computation of the transition probability matrix does not require parametric fitting of a semi-variogram model, (2) asymmetric heterogeneity structures can be modeled because there is no intrinsic symmetry assumption in the coupled Markov chain model, (3) conditioning to measured values is straight-forward, and (4) geological observations and principles (e.g., fining up/down sequences) can be directly implemented in the transition probability matrix. In this extended abstract, we will demonstrate a three-dimensional coupled Markov chain model to characterize subsurface heterogeneity using hypothetical borehole lithology data. |
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Conference Name |
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المؤتمر الدولي الثاني للحقن تحت السطحي : العلم والتكنولوجيا بولاية كاليفورنيا – أمريكا |
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Publishing Year |
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1424 AH
2003 AD |
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Article Type |
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Article |
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Added Date |
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Tuesday, March 6, 2012 |
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Researchers
| عمرو محمد الفقي | Elfeki, Amro Mohamed | Investigator | Doctorate | aelfeki@kau.edu.sa |
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