In mature fields it can often be a challenge to obtain accurate well data and reliable formation parameters without imposing high cost and time constraints on development or production schedules. One common method to test non-naturally flowing wells is impulse testing, which makes use of differential pressures between the formation and a surge chamber or wellbore to perform a short flow period or surge test, followed by a relatively short shut-in period. Unfortunately, these tests frequently result in invalid or uninterpretable data as a result of several uncertainties and test constraints.

An improved version of this common technique encompasses a three-fold approach to optimize the impulse test. A new numerical simulator designs the test to maximize depth of investigation without compromising the interpretable data. The coiled tubing-conveyed intelligent bottomhole assembly used to execute the impulse test may, in certain environments, reduce operating times in comparison to use of conventional tubing-conveyed solutions. The combination of the prejob design package and a functional bottomhole assembly enables consideration of the complexities that can result from impulse testing so that a valid data set is delivered. The interpretation is performed using traditional well test interpretation methodology and an analytical solution specifically designed for impulse testing. This solution considers the wellbore fluid density variation during the test while still maintaining the simplicity of the wellbore model; variable skin is described by an exponential function, thus improving on established analytical methods. A comparison of the results from both interpretation methods establishes the test validity in terms of flow capacity and skin. This paper describes the systematic approach, including its design, execution, and interpretation, and highlights advantages and limitations through the case study and field data of a well in the Wadi Rayan field of Qarun Petroleum Company.

This technique offers a rigless testing method that can optimize test time while delivering valid, accurate results that aid in production forecasting, completion optimization, and planning of remedial intervention for non-naturally flowing wells.

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