Static and Dynamic Uncertainty Management for Probabilistic Production Forecast inChuchupa Field, Colombia

摘要

Structural, stratigraphic, and petrophysical uncertainties resultin a wide range of geologic interpretations. For fields withlong production and pressure history, 3D-dynamic simulationshave been very useful in providing feedback to geologicmodelers, which results in improved static models.The Chuchupa Field has produced 1.9 Tscf of dry gas, orapproximately 40% of the Original Gas in Place (OGIP). Atthe time of this study, 3 new horizontal wells were beingplanned, and new gas sales agreements were being considered.We developed a dynamic workflow to create a range ofprobabilistic simulation models to forecast dry-gas productionunder several production scenarios in the Chuchupa field.Recent seismic re-interpretation, a new stratigraphic study anda revision of the petrophysical model resulted in newprobabilistic static models for the field.While these static models were being built, a parallelnumerical simulation study was conducted to determine therange of OGIP values that could be successfully history-matched.Nine numerical reservoir models were generated byapplying pore volume multipliers to the prior-generationreservoir model, yielding a range of OGIP from 3.8 to 6.6Tscf. We attempted to history match each of these ninemodels by using an optimization routine to adjust aquifersupport, vertical transmissibility across a potential seal, androck compressibility. The optimization routine proved to be avery useful and efficient tool to attain good quality historymatches in short periods of time. Good matches wereobtained for models with OGIP ranging from 4.3 to 5.8 Tscf.Based on this information, the geologic modelers revisedpetrophysical parameters and generated 27 static models.These models encompassed 3 structural interpretations, 3porosity distributions, and 3 possible positions of gas/watercontact (GWC). From experimental design we obtained the P10, P50, and P90 OGIP values of 4.1, 4.7, and 5.3 Tscfrespectively.We scaled up and built reservoir simulation models for 8geologic interpretations to represent the range of OGIP andreservoir geometries. Again, these models were historymatched using the optimization routine. The matchparameters were static well pressures and the absence of waterproduction. Six out of the eight the models could besatisfactorily history-matched with reasonable adjustments toaquifer strength, vertical transmissibility, and rockcompressibility. The OGIP range for these models was 4.1 to5.6 Tscf.We selected 3 models to forecast future gas production.These models match the P10, P50, and P90 OGIP valuesdetermined in the probabilistic static model, and combine thelow, mid, and high structures, porosity and Swi distributions,and the range of GWC positions. We also calibrated thevarious models with historical bottomhole and tubingheadflowing pressures, and coupled the reservoir model with anetwork consisting of surface lines and equipment; pipelinesfrom two platforms to the onshore sale-point station; andmulti-stage compression to 1,215 psia. The model is currentlyused to evaluate various production and market scenarios.