Deconvolution of Wireline Formation Test Data

Abstract Robust methods of deconvolution have been available to the well testing industry recently. This paper investigates the viability of applying a deconvolution algorithm to mini-DST data. A mini-DST test is conducted with a wireline formation tester (WFT) equipped with straddle packers. The use of straddle packers enables an isolated interval from where production can be induced. A mini-DST is actually a small-scale well test with limited entry. The production rate history of a mini-DST has special features. Because the rate of mini-DST is measured close to the source at a downhole location, it is more accurate than measurement from a well test. However, the rate history consists of hundreds of short-term build-ups due to pump characteristics. Special procedures are adopted to address these rate characteristics. Both synthetic and field tests demonstrate that a deconvolution algorithm can be applied to mini-DST data. The application of deconvolution can enhance the radius of investigation. Because deconvolution yields non-unique results, a robust inversion requires at least two build-ups. The data sets selected for deconvolution should be consistent; otherwise, deconvolution will fail. This paper presents deconvolution results of mini-DST data. A deconvolution algorithm is developed to address the characteristics of production rate during a mini-DST test. A comparison study with other deconvolution software is conducted. It proves that deconvolution algorithms work well with mini-DST data.