Modeling technique for generating fluvial reservoir descriptions conditioned to static and dynamic data

One of the characteristic features of fluvial reservoirs is the presence of sinuous sand-filled channels embedded in the background of floodplain shale. In fluvial reservoirs, hydrocarbon reserves are mostly contained in a number of distributed sand bodies isolated by faults or partially connected to one another via good permeability/porosity material but small pathways. This poses special challenges for reservoir modeling because the existence of such connected pathways and barriers between isolated fluvial bodies has great influence on fluid transport and thus production profiles. Detailed knowledge of sand channel geometry, spatial distribution, and connectedness are essential to develop a model that describes fluid flow accurately, predicts the future performance reliably, and helps in decision making.; One aspect of this work was to develop a mathematical foundation to describe multiple channels dynamically and realistically. Another aspect was to incorporate the mathematical formulations into an automated history matching process to enable the calculation of reservoir heterogeneity and sensitivity coefficients as functions of channel parameters.; This work proposed a subcell technique to approach these challenges. We found that this technique provides an efficient method for computing the sensitivity coefficients accurately and serves as a key for fast and effective inversion. The method is capable of supporting a closed-inversion loop matching various sources of static and dynamic data simultaneously. The procedure also enables the assessment of uncertainty associated with the estimated channel geometry, spatial distribution, and permeability/porosity fields.; The application of the proposed technique was demonstrated through several examples in a two-phase, water-oil case. In these examples, the data that was matched included static (geology, geophysics, and petrophysics) and dynamic data such as permanent down-hole pressure and water-oil ratio histories, combined with the information available from 4-D seismic surveys. The resulting reservoir descriptions included multiple channels with different orientation, thickness, width/thickness ratio, length, sinuosity, and permeability/porosity contrast.