Evaluation Techniques for Oil Gas Reservoir Based on Artificial Neural Networks Techniques

By using BP artificial nerve network´s error reversion transmission. Summing up various data of comprehensive logging can solve the problem of low accurate rate for identifying oil, gas, water zones. The software provides nerve network reservoir interpretation model by studying and training the initial data of tested oil. Practice proves the overall coincidence rate of interpretation reaches 97%. It can more efficiently reflects logging technique´s advantage of wellsite quick evaluation oil, gas, water zones. The application in this technique improves the level of logging data interpretation and evaluation.