Oilfield Development Data Quality Control And Application Research

As the development of oilfield delicacy management and the increase of data application extent,data quality has drawn much greater attention to oilfield leaders and professionals.The control of data quality has become the key element to the success of oilfield development and application.Generally,the lack of data management and poor quality will result in a disappointing system far away from clients' expectations.This has been a severe problem,preventing further development of comprehensive study and decision-making.This article first researched the current situation of oilfield database quality,summarized and analyzed the existing problems of the development data,and then built a dimensional model based on various data characteristics and association patterns,to control data quality and to lay a strong foundation for automation.Quality control points are set up in different stages of data's generation-procession-application-decision life cycle,via information-based management methods.Those points will not only help to control data quality from the origin,but also allow professionals to set up key monitoring points according to their responsibilities.This process helps professionals discover and adjust any issues in a timely manner,minimizing the impact of false data remaining in the system,so that data quality control process could reach its optimization.To help research on oilfield data quality control methods and application techniques,a rule model was built using data quality dimension.And then a data quality control examination software driven by the above rule model was established,monitoring data transfer in the overall process.This model will achieve the automation and integration of data quality control,improving the development data to a higher consistent,accurate,integrity and timely level.Along with the implementation of the system,the procedure of data quality management will be optimized gradually,accomplishing full supervision and quality improvement of the data.This further improvement of the data availability ratio,application ratio and application efficiency will take significant effect in operation management and research decision.