Application On Comparison And Analysis Of Oil And Gas Pipeline Inspection Data

In accordance with national regulations and relevant requirements of the enterprise,the pipeline operation company must carry out the pipeline integrity management in the scientific research,design,construction and operation stages.As the most effective technique for integrity evaluation,in-line inspection(ILI)is of great importance to the identification of defects.Using the data comparing with a pipeline in series ILI,can get a wealth of valuable information,including defects' growth,corrosion rate,and further,analyzes the reason of defect formation,assesses the development of corrosion,determines the next round detection time,improves the integrity of the management level.Therefore,a set of reliable methods for data comparison and analysis in oil and gas pipelines is theoretical and practical significance for guaranteeing the intrinsic safety of pipelines,ensuring the integrity of pipelines,and reducing the loss of personal and property.Due to the uncertainty of some factors and errors and the diversity of the multi detection processes,some of the test results are inconsistent with the excavation,and there is the possibility of false call.For this reason,a series of algorithms were proposed—such as ILI Proofreading Algorithm for the Initial/Termination Position,Seam Data Alignment Algorithm Based on Data Mining,Misalignment Weld Type Judgment Fuzzy Intelligent Algorithm Based on Bayesian Theory,Genetic Algorithm Theory and Fuzzy Clustering—through which the exact matching work of the report features has been completed.By analyzing the characteristic comparison results,the calculation method of corrosion growth rate was studied.The growth rates of various characteristics were calculated by the Direct Method.But in view of the Direct Method,both the growth size and the growth cycle were estimated so that there are mutual interferences between two processes.Then cluster analysis technique and Bayesian theory were introduced to estimate the actual depth of defects that a method was recommended,which was named “Corrosion Growth Rate Estimation Based on Clustering Technique and Bayesian Model Framework”.The recommendation method made the two estimation processes be independent,and eliminate the interference.In order to provide feedback to ILI operators and manufacturers,test result was evaluated,and the performance index(PoD,PoFC,PoI,SE etc.)of the ILI tools were evaluated.The completed pipeline defect data comprehensive evaluation method can help the pipeline operators to select the tool and facilitate the improvement the tool.Meanwhile,to assist the above research work,“Oil and Gas Pipeline Inspection Data Comparison Analysis System” was developed,to dispose and analysis of massive data.This system consists of 7 modules: Project Management,Data Entry,Data View,Weld Alignment,Feature Matching,Feature Comparison,Corrosion Growth Rate Calculation.