Identifying Abberant Segments in Permanent Downhole Gauge Data


Emuejevoke Origbo







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Data from permanent downhole gauges are needed for interpretation of subsurface conditions in a well. The data from permanent downhole gauges are voluminous and usually contains aberrant segments. Using this aberrant data to characterize the reservoir leads to generation of inaccurate reservoir parameters (permeability, skin and storage). The approach used in this work to solve the problem of interpretation of permanent downhole gauge data was by generation of multisegment synthetic pressure data using the pressure equation with all the reservoir parameters known. An aberration was introduced in the form of a pressure segment that went against the reservoir physics; it decreased with a production shut in, when it should increase. An algorithm based on direct Kalman filtering technique was developed which was independent of the reservoir model and extracted a signal with the minimum error (mean square deviation) from the noisy/aberrant signals. In this way, aberrant segments were successfully identified, removed and the original signal with actual reservoir parameters recovered.

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