Well monitoring from om-the-fly analysis of data from Permanent Downhole Gauges (PDGs)

Abstract

The thesis focuses on time-lapse Pressure Transient Analysis (PTA) of data acquire with Permanent Downhole Gauges (PDGs). The objective is to develop and test approaches in automation of time-lapse PTA. Helping in providing well-reservoir parameters such as reservoir flow capacity (Kh) and well skin (S) is analyzed. A short review of modern PDGs with description of their specifications (i.e. accuracy, resolution) is followed by literature review of recent paper focused on automating time-lapse PTA. This includes machine learning and multi-well interpretation. The main part of the thesis begins with the description of the code developed in combination with analytical solutions used for time-lapse PTA interpretations. The thesis continues with analysis of a synthetic injection well simulated in Saphir. And end up with testing the code with an actual history well production on the Norwegian Continental shelf. The results of the test on the synthetic well example have shown that from two flow capacity calculation procedures using semi-log and log-log derivative analyses. The last one provides more accurate results on flowing transients. The estimated well skin depends on the flow capacity estimation above. Therefore, is also better estimated with the log-log (derivative) analysis. Both methodologies behave similar in shut-in cases. The inclusion of superposition time when estimating parameters was demonstrated to be a determinant factor. The tests on the actual well showed that the code provides similar results with Saphir, where the automation routines gives values with an error of 12% and 6% for the semi-log and derivative analysis respectively.