Considering the imminent end of the ‘easy oil’ era, the increasing demand for energy and the global push towards the energy transition, oil and gas companies are more than ever interested in sustainable ways to develop marginal and complex hydrocarbon fields economically, through the application of technology and maximization of data analysis. In small partially appraised fields where the cost of drilling an appraisal well could derail the project economics, it becomes necessary to sweat the limited data available for reservoir modelling. The uncertainty analysis must be robust enough to ensure that the adopted field development strategy would yield a positive net present value despite the wide uncertainties associated with the field. The conventional workflow for subsurface uncertainty modelling involves defining the uncertainty ranges of static and dynamic reservoir parameters based on a single reservoir model concept. This paper focuses on a marginal field case study where the multi scenario modelling approach was adopted. This approach considered alternate reservoir geologic concepts based on different interpretations of the reservoir architecture, taking full cognizance of the available data, reservoir uncertainties and regional geology knowledge. Field Alpha is located onshore of Niger Delta in Nigeria. The geologic setting consists mainly of multi-storey, complex channel-belt systems, incising through Shoreface deposits. The reservoir of interest is an elongated structure with only two well penetrations located at the opposite distal part of the structure. The key reservoir uncertainties are reservoir structure, architecture, connectivity, and property distribution. Two possible distinct architecture were interpreted based on regional correlation and seismic. This paper focuses on how the interpretations and other information informed a robust development strategy that yielded significant (30 %) reduction in development cost and positive net present value.

Material balance analysis is a proven technique for quantifying reservoir performance. Reliable material balance analysis requires accurate pressure and production data amongst other things. In cases where complete production data is not readily available, estimating reservoir performance properties such as pressure and fluid contacts which is needed to support further field development can be a serious challenge. This paper shows how the issue of scarcity of production data can be managed to enable proper reservoir analysis to support further field development. The paper focuses on a case study on the Ibaba reservoir where paucity of production data is a key uncertainty. The Ibaba reservoir is a Niger Delta reservoir with two parts, Part A and Part B. Both parts have been produced simultaneously from the field for over 40 years. There is a need to carry out material balance analysis on the reservoir to estimate the current fluid contacts to support Short Term Oil Generation activities (STOG). This exercise required production data from inception to the current year 2016. However, for the wells produced in Part B of the reservoir, complete production data was not readily available. To solve this problem, complete production data was generated by performing decline curve analysis on the available production data. A robustness check was carried out and this gives confidence in the results obtained.