The Petroleum Drilling Accident Diagnosis System Based On RDT & FDF

Base on the deep research of present situation on domestic oil drilling engineering accident diagnosis this paper has analyzed the problems in this field. There are two main reasons lead to the not so good drilling accident diagnosis effect:Firstly, the catch of sensor signal abnormalities is not accurate or in time so that lead to the system would neglect the change of the sensor signal abnormalities. Secondly, many researchers use foreign advanced method in the drilling engineering accident diagnosis and forecast in spite of whether or not fit to domestic geological particularity technology level. When some accident happened in the well, these methods can not make an accurate forecast.To deal with the two problems above, a new drilling engineering accident diagnosis and forecast method based on based on RDT&FDF (Related Dynamic Threshold and Fuzzy Data Fusion) is proposed in this paper. Main tasks in this paper are as follows:Firstly, this paper introduces the all kinds of sensors in the drilling process and their effect. And then the reason and danger of drilling accident are expounded in the next paragraph. In the end of the first part this paper states the sensor reflections when the accident happened in the well.Secondly, this paper rise up the accuracy on the catch of sensor signal abnormalities while using the related dynamic threshold method. At the same time, contrast with application of D-S Evidence theory, neural net and gray theory in the drilling accident diagnosis, the method based on fuzzy data fusion is much more close to the characteristic fuzziness and uncertainty of the drilling process.At last, the petroleum drilling accident forecast system contains two main parts:data processing module and diagnosis module. In this part, database design, drilling parameters calculation process and middle parameters of the accident diagnosis is introduced and the result is given in the last part of this paper.After testing the new method has a good capacity to catch of sensor signal abnormalities and can change the threshold of the sensor in the different drilling stage or in the different rock stratum. Meanwhile, this method combines the artificial experience with the software accident diagnosis to ensure the accuracy of the accident forecast result.