The application of ANN for zone identification in a complex reservoir
- and others
Reservoir characterization plays a critical role in appraising the economic success of reservoir management and development methods. Nearly all reservoirs show some degree of heterogeneity, which invariably impacts production. As a result, the production performance of a complex reservoir cannot be realistically predicted without accurate reservoir description. Characterization of a heterogeneous reservoir is a complex problem. The difficulty stems from the fact that sufficient data to accurately predict the distribution of the formation attributes are not usually available. Generally the geophysical logs are available from a considerable number of wells in the reservoir. Therefore, a methodology for reservoir description and characterization utilizing only well logs data represents a significant technical as well as economic advantage. One of the key issues in the description and characterization of heterogeneous formations is the distribution of various zones and their properties. In this study, several artificial neural networks (ANN) were successfully designed and developed for zone identification in a heterogeneous formation from geophysical well logs. Granny Creek Field in West Virginia has been selected as the study area in this paper. This field has produced oil from Big Injun Formation since the early 1900`s. The water flooding operations were initiated in the 1970`s and are currently still in progress. Well log data on a substantial number of wells in this reservoir were available and were collected. Core analysis results were also available from a few wells. The log data from 3 wells along with the various zone definitions were utilized to train the networks for zone recognition. The data from 2 other wells with previously determined zones, based on the core and log data, were then utilized to verify the developed networks predictions. The results indicated that ANN can be a useful tool for accurately identifying the zones in complex reservoirs.
- OSTI ID:
- 182256
- Report Number(s):
- CONF-950983-; TRN: 96:000714-0005
- Resource Relation:
- Conference: Eastern regional conference and exhibition of the Society of Petroleum Engineers: natural gas - the fuel for the future, Morgantown, WV (United States), 19-21 Sep 1995; Other Information: PBD: 1995; Related Information: Is Part Of 1995 Eastern regional conference and exhibition; PB: 222 p.
- Country of Publication:
- United States
- Language:
- English
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