Abstract
Obtain accurate, reliable and complete single-well monitoring data is important task of oilfield dynamic monitoring. At present, oilfield dynamic monitoring technology has become more and more mature, but it is impossible to cover every single-wells or every horizons. Thus, the single-well monitoring data is not continuous, and the missing phenomenon is widespread. To solve this problem, this paper proposes a new combined interpolation algorithm based on SPSS which presents five missing data processing methods and cubic spline interpolation, and applied to a single-well monitored missing data processed. The numerical experiment shows that the new algorithm has the highest precision, and it as an effective approach for interpolating the missing data of single-well monitoring.
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Xie, Xj., Zhao, Mc., Lu, Ll. (2016). Combined Interpolation Method for Single-Well Monitoring Data. In: Cao, BY., Wang, PZ., Liu, ZL., Zhong, YB. (eds) International Conference on Oriental Thinking and Fuzzy Logic. Advances in Intelligent Systems and Computing, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-30874-6_36
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DOI: https://doi.org/10.1007/978-3-319-30874-6_36
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