Evaluation of New Well Impact on Existing System Via Integrated Asset Modelling: A Case Study from Ordos Basin Tight Gas Field

Abstract

Abstract The production rate from low-permeability wells often declines rapidly during their lifespan, and from the field level, new wells are continuously planned and added to the existing production system. Previously, the impact of the new wells on the existing system, including surface and subsurface systems, is typically evaluated with standalone models, which often results in inconsistency and discontinuity. To resolve this issue, this paper introduced an integrated asset modelling (IAM) method to a gas field in the Ordos basin, China, and the results are continuous and consistent. Changqing oilfield operates in Ordos basin, and it is currently the largest oil and gas field in China. Most of the gas reservoirs are tight and the gas production rate of each well decreases rapidly during the production phase. Thousands of new wells are drilled each year to maintain the total production from the field. To better evaluate the impact of those new wells, this paper introduced the IAM method to field Block-S, where more than one hundred wells were drilled and completed in an area of 150-km2. The typical features of wells in the Block-S reservoir are more than 3000-m deep, underpressurized, and have low permeability of less than 3.5 md. The subsurface, wellbore, and the pipeline models were prepared, history matched, and calibrated separately with geology data, production history, and various measurements. A standard IAM connector was used to couple the reservoir model and the production network by mapping parameters from both sides, e.g., pressure, inflow performance, liquid density, oil/gas ratio, and water/gas ratio from the reservoir model are passed to production network, while the gas flow rate from the network model is fed back to the reservoir numerical model as a control mechanism at a time step of 3 months. The coupled system is more realistic than the standalone simulations used previously, and it showed new insight into the production dynamics during the field development. In this study, several IAM examples are shown, which impact the operator’s decision making, including the use of a choke, the configuration of the compressors, and the tie-in location of the new well clusters. Overall, IAM allowed the operator to properly evaluate the impact of the new wells on the existing system, based on which the operator can optimize the engineering aspect of the new wells. The IAM concept and practice are also suitable for many other gas fields or underground storage scenarios.