Analytical Approach for Development Plan Optimization for Fields at Early Development Stage – Case Study in the Greater Burgan Field
Authors: Naqy Amnah , Mammadli Ilkin , Zhang Pinggang , Stigliani Roberto , Rastogi Vandena , Al-Shammali Adnan 
Published: February 2025

Greater Burgan Field consists of stacked primary sandstone and secondary carbonate reservoirs. Long-term decisions for reservoir health management, investment value, and water handling projects are all based on the ability to accurately predict and forecast production profiles. Secondary reservoirs are often more geologically complex, with less dynamic production history, making these forecasts even more challenging. Such complexities necessitate innovative approaches to address uncertainties and provide reliable forecasts, especially during the early stages of development.

This paper aims to highlight methods and workflows implemented by the South East Kuwait (SEK) reservoir team to improve the efficiency of production forecasting, using the Upper Wara reservoir as a case study. The Upper Wara reservoir is notable for its geological intricacies, including channels, heterolithics, and bay fill deposits. It is still in the early-development stage, and many wells have commingled production with historically important Middle and Lower Wara formations. This commingling further complicates data isolation efforts, requiring tailored approaches for meaningful insights. Unravelling and isolating enough dynamic data specific to Upper Wara to feed a traditional full-field simulation model would be too time-consuming and still include many uncertainties. Instead, the team utilized an analytical approach to provide fit-for-purpose predictions within a significantly shorter timeframe. In addition, the team also wanted to explore optimum well spacing and the voidage replacement ratio for the waterflood scheme, so built a dedicated sector model to answer these business questions. The well performance type curves were defined for variable sand qualities using this sector model. This enabled better categorization of reservoir characteristics and their corresponding impacts on well behavior. An analytical spreadsheet tool was created to run sensitivities and to scale up the profile to account for field-wide volumes.

The effectiveness and accuracy of the analytical workflows were checked and compared with the sector model across multiple scenarios to build confidence in this approach. These new tools were confirmed fit-for-purpose for Upper Wara early-stage development planning, building confidence in plausible predictions within an acceptable range of uncertainty and ultimately allowing for long-term investment decisions such as well count, pattern flood strategy, and facilities planning in a much shorter timeframe than traditional approaches would have allowed. This expedited process not only saved valuable resources but also ensured timely decision-making critical for the reservoir’s strategic development.

The team recommends further work in the Upper Wara to conduct a waterflood pattern pilot in different geological settings within the field for further calibration enhancement and to integrate this understanding with the existing full-field reservoir simulation model with stacked reservoirs of the Greater Burgan Field. Such integration will enhance predictive accuracy and establish robust frameworks for managing secondary reservoirs.

This analytical approach has been proven successful and could be quickly implemented across other secondary reservoirs of the Greater Burgan Field to optimize future investment decisions, as well as many other reservoirs at pre-development or early-development stages across Kuwait. Its adaptability makes it a viable solution for addressing challenges in reservoirs with limited historical data and complex geological settings, offering significant potential for broader applications.