STRATIGRPAHIC SIMULATION USING FUZZY LOGIC TO MODEL SEDIMENT DISPERSAL
Robert V. Demicco and George Klir
Fuzzy logic was initially developed by systems engineers in the 1960s. Since the 1980s, fuzzy logic has been extensively used in robotics control and is one of a number of emerging, very powerful, "soft computing" techniques. Scientists have recently started to adopt fuzzy logic to solve a variety of complicated physical, chemical and biological problems. The purpose of this research is to use fuzzy logic to model sediment production, erosion, transportation and deposition to produce synthetic stratigraphic models of how sedimentary rocks are deposited in subsiding basins. Using fuzzy logic instead of more traditional numerical solutions to partial differential equations holds the promise of rapid and efficient modeling of extremely complex natural processes which heretofore were intractable or required extensive computational power. In addition, because fuzzy logic is based on natural language, it is easy to understand and use. Moreover, fuzzy logic is computationally efficient, and allows many different combinations of input variables to be modeled rapidly. The utilitarian goal of this research is to produce synthetic geologic cross sections which can be compared to incomplete data sets (such as drill core data or shallow seismic data). The complete model stratigraphy can then be used to "fill in the gaps" to give exploration geologists or engineering geologists the information they need to better explore for and exploit hydrocarbon resources or design remediation plans for contaminated groundwater plumes. From a theoretical standpoint, synthetic stratigraphic models increase our fundamental understanding of how sedimentation varies in space and time in response to tectonic processes, sea level changes, climatic changes, and other environmental variables.
