Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. Final report, August 31, 1997
The primary goal of the project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlations between wells. Using the correlations and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained. Although all the components within the overall system are functioning, the integration of dynamic data may not be practical due to the single-phase flow limitations and the computationally intensive algorithms. The future work needs to concentrate on making the dynamic data integration computationally efficient.
- Research Organization:
- Tulsa Univ., OK (United States)
- Sponsoring Organization:
- USDOE Assistant Secretary for Fossil Energy, Washington, DC (United States)
- DOE Contract Number:
- AC22-93BC14894
- OSTI ID:
- 587949
- Report Number(s):
- DOE/BC/14894-15; ON: DE98000465; TRN: AHC29809%%49
- Resource Relation:
- Other Information: PBD: Mar 1998
- Country of Publication:
- United States
- Language:
- English
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