Successful Integration and Interpretation of Different Sources of Data and Utilization of Seismic Attributes to Reduce the Level of Uncertainty in Infill Planning

Abstract The Greater Burgan Field is located onshore southern part of Kuwait and it is the world's largest clastic field. A low-relief anticlinal dome draped over a basement horst structure defines it. The primary producing reservoirs are the Wara and Burgan of Cretaceous age. Burgan field has been developed by drilling more than 1000 wells mainly targeting Burgan reservoir. Majority of the wells were planned and drilled in the low risk / low uncertainty part of the field, where the combination of the shallow structure and good quality reservoir facies allowed drilling till date. Since the wells density has increased in the dome area and the area congested with surface facilities, biggest challenge lies in identifying locations in the flank and rising flank part of the field. As the demand for oil increases rapidly and the need to sustain production from ageing wells is necessary, more new wells needed. Placing increased number of infill wells, while maintaining the proper reservoir management is a major challenge. In order to plan the wells in a way that maximizes the productivity and optimizes the economy; a study was conducted to analyse the density of the wells and the impact on reservoir behaviour. This comprehensive study targeted area "A" which is in the middle of the field, that is characterized by it's well developed facies, massive oil column and the lateral connectivity of the sand. Well correlations, OWC movement, production rates, density of the wells and the spacing were extensively analysed and a way forward for new infill and well planning was established. The established way forward used to plan the new infill and to design the trajectory of the wells. Based on that new locations were identified to be drilled away from our comfortable area ranging from low to high-risk locations, where the highly heterogeneous sands and the relatively low structural levels increased the level of uncertainty adding to that the chances of oil might be already drained by the offset up dip wells. In order to lower the level of uncertainty several seismic attributes were included in the planning phase. One of the powerful attributes used is the genetic inversion, which is adopting the same approach as the neural network. Two different seismic volumes differ in the size were trained using well logs data, then QCed with the existing wells. The smaller seismic volume was highly correlatable to the actual data and more reliable compared to the larger volume. The integrated volume was used in the locations identification and planning process. Subsequently all the identified locations released planned and drilled within one year. The results were promising as the encountered oil column in each well exceeded our expectations considering the high risk factor presented in each location. These findings has opened the door to investigate more and widely in the challenging or unestablished part of the field where good opportunities still exist in the structural trends/unestablished part of the field, where minor faults and various facies changes act as a barrier for oil accumulation. The aim of this paper is to shade some lights on the current challenges in the Brown field development and to emphasize on "No risk no gain". This comprehensive paper will illustrate the importance of proper data integration, the methodology used in the well planning and the successful post drilling results, the results of this study will guide on the future infill drilling.

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