On The 2D Dynamic Models for Production Forecasting of Chemical EOR

An aggressive timeline for delivering chemical Enhanced Oil Recovery (cEOR) projects is critical as the transition towards renewable energy in the near future has become an international obligation. Therefore, there is a growing need for a simplified yet fit for purpose production forecasting approach. Additionally, as the number of chemical EOR field implementations increases within the industry, more field data becomes available, providing increasingly better performance benchmarking for new projects. Using such benchmarking in combination with the simplified forecasting approach allows for obtaining an acceptable quality forecast at low costs. In the current work, we present the computationally inexpensive 2D modelling approach and the guidelines governing its use in accordance with Integrated Reservoir Modelling (IRM) workflow.

In the IRM workflow, knowing the trade-offs between the conventional 3D and the simplified 2D modelling approaches is essential. As a result, we first start discussing the pros and cons of the 2D modelling approach. Then, we outline in detail the guidelines for constructing 2D models, which are divided into four steps: Data Analysis, Building 2D Models, History Matching, Forecasting, and Calibration. Finally, we present real case studies where the approach has already been applied to several chemical-enhanced oil recovery projects in Southern assets.

Unlike conventional 3D models, 2D models simplify the reservoir by reducing dimensionality and focusing on key features such as stratigraphy and structural geology along a cross-section. It reduces the computational cost, enabling faster simulation runs and better grid resolutions. In the early Data Analysis step, it is also important to demonstrate evidence that the oil displacement process is predominantly two dimensional. Examples of such a process could be a) the reservoirs under the bottom aquifer developed by horizontal wells and b) layered cake structure reservoirs with insignificant crossflow developed by pattern waterflooding and vertical wells for oil production. This publication presents the results of the Nimr-E and Amin Polymer study cases, where the displacement process resembles the former displacement concept. The results of the Marmul ASP study are presented to demonstrate the application of the 2D modeling approach to the latter displacement concept.

2D models capturing the essence of the oil recovery process are powerful and cost/time-efficient reservoir engineering tools that should be used for predicting the performance of oil fields under different production stages. Implementing such an approach will accelerate the project’s dynamic workflow and help make quick economic decisions.