CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS

TANG Ping

doi:10.11781/sysydz200304413

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Article Navigation > PETROLEUM GEOLOGY & EXPERIMENT > 2003 > 25(4): 413-416

TANG Ping. CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2003, 25(4): 413-416. doi: 10.11781/sysydz200304413

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TANG Ping. CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2003, 25(4): 413-416. doi: 10.11781/sysydz200304413

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CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS

doi: 10.11781/sysydz200304413

TANG Ping

Research Institute of Exploration and Production, SINOPEC, Beijing 100083, China

Received Date: 2003-01-17
Rev Recd Date: 2003-06-20
Publish Date: 2003-07-25

Abstract

Abstract

The neural network has been widely used in reservoir parameter calculation with logging data and has got good effects. But under the control of logging data from multiple wells, it is crucial to construct a unified mathematical model, which helps to promote the contrast of calculating outputs among all the wells and in turn to promote the accuracy of interwell prediction. Based on the edition, standardization, normalization and depth correction of logging data, this research constructed a unified BP neural network model for each sand group. Compared with real samples, the predicting effect was good.
- mathematical model,
- reservoir parameter,
- logging,
- neural network

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CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS

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CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS

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