Research On Leak Quantitative Monitoring Method Of Submarine Oil And Gas Pipeline Based On Multi-beam Sonar

With the exploration and development of oil and gas fields,China faces an increasing risk of underwater oil/gas spills,and techniques such as predictive monitoring and disposal during underwater oil/gas spill response have become more challenging.As a result,estimating the temporal variability of the flow rate and volume of gas escaping from the seabed has become a challenge,and continuous acoustic monitoring of the seabed is one way to address this issue.In this paper,we investigate the method of monitoring the velocity and flow rate of oil and gas leaks in multibeam water images,develop an oil and gas velocimetry software combining particle velocimetry process and software engineering techniques,and estimate the flow rate of leaking oil and gas using forward and inverse methods.Firstly,the principles of water body imaging for multibeam bathymetry systems are described;secondly,the focus is on a restricted contrast adaptive histogram equalisation algorithm based on a variety of feature extraction methods based on water body images as a means of improving the contrast of the images.Various methods for velocimetry of moving targets are investigated,and oil and gas velocities are estimated based on the PIV particle velocimetry principle;the Medwin model is combined with backscattering data from bubble swarms to estimate the flow of leaking gas.The results from pool tests show that the acoustic and optical measurements are similar and match well with the actual simulated release results.Secondly two schemes are used to detect leaking oil and gas based on motion information based on multibeam sonar water images,the pool and lake results show the effectiveness of the method in this paper.Finally the oil and gas velocimetry software is designed and implemented including data acquisition module,feature extraction module,velocity measurement module,post-processing module,etc.The functions of each module are verified and the histogram statistics of frequency distribution of velocity are realised.After a variety of experimental data processing and result analysis,the optical and acoustic images were compared and verified,and the tested oil and gas velocity estimation software met the expected requirements in terms of function and algorithm.The validity of the algorithm was verified by comparing the actual values in the flow meter through the forward and inverse method for flow estimation.