No abstract

Sand control decisions are often made based on a deterministically predicted Safe Drawdown Pressure (SDP) without proper regard to the amount of uncertainty associated with the value of SDP. These uncertainties can be large when planning a Drillstem Test (DST) for a deepwater exploration well. On one hand, predicting too low of a SDP for a DST can result in unnecessary sand control. On the other hand, predicting too high of a SDP can lead to sanding during the test, which can cause numerous problems and ultimately cost much more than a sand control installation. Thus, a probabilistic study is warranted to quantify the expected sanding risk through a SDP probability profile, which can be used to estimate the risked expected value of a decision to install sand control or not.In this study, data from 12 offset wells in nearby blocks from an Offshore Nigeria exploration well were reviewed. First, a regional geomechanical model (in-situ stress, pore pressure and rock mechanical properties) was calibrated and validated based on offset data. The calibrated geomechanical model was used with a sanding prediction model and was calibrated and validated based on offset DST and sand control data. Next, a statistical analysis of regional in-situ stress, sand pressure and rock properties for different sand intervals was performed to generate the necessary Probability Distribution Functions (PDF) and used as inputs to a SDP Monte Carlo simulation. And finally, a deterministic approach was also used to predict SDP. A comparison of Monte Carlo simulated SDP distribution and the deterministically predicted one from offset wells indicates consistent results. The SDP PDF allows estimation of the expected values for installing sand control or not and improves judgments of the true cost of obtaining the DST information.