Novel Application of QuantiMin SQP Methodology for Improved Reservoir Characterization in a Deepwater Turbidite Field Development

Abstract The success of any green as well as mature field development planning and execution lies in the ability to recreate the environment of deposition with the appropriate spatial and temporal facies interdependencies. This, when done with proper application of the varied suite of geotechnical software/knowhow, often leads to the creation of a finite number of high resolution and equiprobable reservoir models within a macro and micro sedimentological framework, that readily lends itself to optimized risk and uncertainty management. This becomes even more critical in deepwater turbidite systems where the impact of geologic uncertainties can significantly reduce project value and does often prevent marginal field developments in the absence of a low cost tie-in option. This paper presents the novel application of one such technique; the QuantiMin methodology approach improves aspects of reservoir characterization and facilitates various aspects of well and reservoir management in the waterflood development of a Miocene deepwater turbidite system in the Gulf of Guinea. The QuantiMin technique is a sequential quadratic program that solves non-linear problems by series of quadratic programming steps. When applied in this context, it assesses the mineral and fluid content around the near wellbore area, based on their unique well log responses, and returns with a finite volume distribution of mineral and fluid distribution around the wellbore, using the mineral and fluid distribution input from appraisal well cores as the calibration or control variable. The results from QuantiMin analysis have been used in this field to: Evaluate the potential impact of mineralogy on the performance of water injection wells. Apply understanding of mineral types around the wellbore to the design of acid stimulation recipes. Develop a framework for understanding the field scale distribution of heterogeneities by establishing the interdependencies between log-scale QuantiMin and microscopic core petrography data, and hence facilitate high resolution reservoir characterization. Establish realistic flow potentials for development wells.