An Investigation into Non-Reservoir Components that Undermine Reservoir Responses in Transient-Test Data

Abstract

Abstract Transient-test data can be significantly affected by subtle non-reservoir noise generated by natural or operational factors. The impact of such noise on the pressure-transient analysis depends on the signal-to-noise ratio achieved during transient tests. Often, a misleading interpretation of the reservoir characteristics can result. This study will quantify such effects on the interpretation results by evaluating the signal-to-noise ratio as in wireline testing operations, deep transient testing, drill-stem testing and production testing. Effects of non-reservoir factors can be difficult to identify, and often may lead to misrepresentations or misinterpretations. Analytical and numerical reservoir simulations will be used to illustrate quantitative criteria of defining the acceptable operating conditions and preferable techniques for pressure-transient-tests, depending on the reservoir characteristics. Convoluted effects of noise, drift, resolution, periodic tides have been quantitatively evaluated to demonstrate the situations when the reservoir signal is too weak to achieve meaningful characterization. Different pressure-transient techniques will be evaluated with a focus on the signal-to-noise ratio. Certain disruptive behaviors of equipment and nature tend to distort the measurements performed during such tests. Depending on the amount of disruption caused in the measurements during the tests, there are situations when the test objective may not be achieved at all. Failure to create dominant reservoir responses can result from an insufficient signal-to-noise ratio with the rate of production and pressure drawdown. It is a function of formation and fluid properties and/or mechanical environment. A minimum rate of production is needed for creating a necessary magnitude of signal-to-noise ratio to interpret correctly the reservoir response. The paper will help determine the minimum rate of production and the duration of flow needed to obtain the presence of deep heterogeneities or boundaries with a reasonable level of certainty. If a test is run with a rate lower than the critical value, for example, the data will be biased by other hardware or natural factors that are unrelated to the reservoir signals. Illustrative examples will also be presented to show how misleading characteristics of the reservoir and the well can be deduced without sufficient signal-to-noise ratios. This study will quantify the non-reservoir factors by evaluating the corresponding signal-to-noise ratios. As a result, a practical guide will be created for selecting a proper testing method from a quantitative point of view.