In drillstem testing (DST), analyses of transient data are generally restricted to the post-cleanup period because rates often go unmonitored at early times during the cleanup phase, unless aided by multiphase flow metering. The value of early-time production data monitoring may be overlooked for two reasons: first, transients may be difficult to interpret because of two-phase flow in the formation; second, two-phase flow metering becomes a requirement. The objective of this study is two-fold: to estimate rate from distributed-temperature sensor (DTS) data available for downhole telemetry with a rigorous transient analytical model, and to use the computed rates to perform transient analysis for both the pre- and post-cleanup periods. Comparing and contrasting permeability estimates from the two periods provides guidance on the suitability of this approach. To that end, this study compares and contrasts rate computation with analytical methods. The new methods entail transient-temperature modeling with and without superposition effects. Two field examples strengthened the new rate-computation methods introduced here, and simulated examples probed the possibility of extracting meaningful information from the cleanup data.

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Operators often avoid conventional drill-stem testing (DST) in offshore environments because it is costly and its value lacks transparency. Short-duration tests may be a promising alternative to conventional DSTs for learning formation conductivity, but they should not be restricted to exploratory wells. Short-duration tests can have a profound impact in any deepwater field-development setting. Stakes are high when unfavorable productivity and injectivity indices may change the well count calculus. Tools such as formation testers provide a credible alternative, but closed-chamber tests (CCT) and/or slug tests are also helpful for situations in which large volumes of formation fluid are sampled. Given that short-duration tests (CCT and slug) can last only a few minutes—particularly in high-conductivity reservoirs—we approached the challenge with a two-fold strategy. First, we developed a forward model to design the chamber length to ensure that we collected interpretable test data. Second, we combined the CCT and slug tests so that we could control the total test duration, particularly in high-conductivity reservoirs. The approach presented here allowed individual treatment of slug, CCT, and reverse-slug or injection test for underpressured reservoirs. Overall, the model presents a simple, yet complete approach to design and analysis of these short-term tests.

Reservoir relative permeability and capillary pressure, as a function of saturation, is important for assessing reservoir hydrocarbon recovery, selecting the well completion method, and determining the production strategy because they are fundamental inputs to reservoir simulation for predicting lifetime production of a well. Estimation of relative permeability and capillary pressure curves at reservoir conditions is also an important task for successful planning of waterflooding and enhanced oil recovery. The relative permeability and capillary pressure data estimated from core analysis might cause concern regarding representativeness, and adjustments are typically necessary for successful production forecasting. This paper proposes a new method to obtain relative permeability and capillary pressure curves with downhole pressure-transient analysis (PTA) of mini-drillstem tests (miniDSTs) and well log-derived saturations. The new approach was based on performing miniDSTs in the free water, oil, and oil-water transition zones. Analyses of the miniDST buildup tests provided absolute formation permeability, endpoints of relative permeability to both oil and water, and curvature of the relative permeability data. Additionally, resistivity, dielectric, and nuclear magnetic resonance (NMR) logs were used to determine irreducible water, residual oil, and transition zone saturations. Combining these downhole measurements provided the relative permeability and capillary pressure curves.