Abstract
Creating reservoir model that is accurate requires extensive data and enormous computing resources. As these resources are often not available, this study proposes a workflow (& corresponding case study) to generate box reservoir models that require minimum data yet yield reasonable results.
Field Lima has two wells Lima-1 & Lima-2 (down-dip well) that produces gas from Sand-B which is a moderate water drive reservoir. After producing gas naturally, Lima-2 watered-out while Lima-1 still produced gas. To curtail the increase of Water Gas Ratio (WGR) in Lima-1, a coproduction technique was evaluated. The intent was to produce water from Lima-2 at high rates to reduce WGR increase in Lima-1. This required reservoir simulation to predict if producing water from Lima-2 will limit aquifer encroachment at Lima-1 and justify the additional CAPEX required to install water handling facility at Lima-2. As Lima is a marginal field, available dataset only included; initial reservoir pressure, production history and standard open-hole logs. No permeability, aquifer or pressure history data was available. Therefore, a workflow was formulated to create a reservoir model that can predict production rates of Lima-1 using available data within engineering accuracy.
Firstly, the pressure history was created using recorded flowing wellhead pressures and wellbore hydraulics model. Further, a tank model was created for the reservoir using material balance software and cumulative productions of both wells were used as unique data to calibrate the model. This was used to calculate the aquifer properties. Fractional flow models & Corey correlations were used to estimate relative permeability data. All this derived data was then used as input in the reservoir simulator, where a localized block grid was created using depth-structure maps of Sand-B. The model was history matched using production data of Lima-1 & Lima-2 and aquifer movement was calibrated using water breakthrough in Lima-2. Finally, the model was run to predict production rates of Lima-1 with & without keeping Lima-2 on production to evaluate if co-production technique was effective.
The model predicted that Lima-1 will be able to deliver its production targets even without keeping Lima-2 on production suggesting that extra CAPEX required for co-production was not justified. Forecasted gas rates for Lima-1 matched the actual gas rates with around 10% error. The accuracy of forecasted results endorses the use of box reservoir models to undertake economic decisions, in scenarios where lack of time & data doesn’t allow creation of detailed dynamic reservoir models.
