Quantitative basin modeling: present state and future developments towards predictability


Tuncay K., Ortoleva P.

GEOFLUIDS, cilt.4, sa.1, ss.23-39, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 4 Sayı: 1
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1111/j.1468-8123.2004.00064.x
  • Dergi Adı: GEOFLUIDS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.23-39
  • Anahtar Kelimeler: basin modeling, fluid flow, rheology, GEOCHEMICAL SELF-ORGANIZATION, ASSESSING NAPL CONTAMINATION, MULTIPHASE FLOW MODEL, FINITE-ELEMENT-METHOD, REGIONAL JOINT SETS, FLUID-FLOW, SEDIMENTARY BASINS, PRESSURE SOLUTION, GAS GENERATION, GROUNDWATER CONTAMINATION
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

A critique review of the state of quantitative basin modeling is presented. Over the last 15 years, a number of models are proposed to advance our understanding of basin evolution. However, as of present, most basin models are two dimensional (2-D) and subject to significant simplifications such as depth- or effective stress-dependent porosity, no stress calculations, isotropic fracture permeability, etc. In this paper, promising areas for future development are identified. The use of extensive data sets to calibrate basin models requires a comprehensive reaction, transport, mechanical (RTM) model in order to generate the synthetic response. An automated approach to integrate comprehensive basin modeling and seismic, well-log and other type of data is suggested. The approach takes advantage of comprehensive RTM basin modeling to complete an algorithm based on information theory that places basin modeling on a rigorous foundation. Incompleteness in a model can self-consistently be compensated for by an increase in the amount of observed data used. The method can be used to calibrate the transport, mechanical, or other laws underlying the model. As the procedure is fully automated, the predictions can be continuously updated as new observed data become available. Finally, the procedure makes it possible to augment the model itself as new processes are added in a way that is dictated by the available data. In summary, the automated data/model integration places basin simulation in a novel context of informatics that allows for data to be used to minimize and assess risk in the prediction of reservoir location and characteristics.