The characterization of a reservoir’s internal architecture is a major challenge, especially during the reservoir appraisal phase when the information is limited. At this stage, all the uncertainties affecting the quantity and distribution of hydrocarbons in the reservoir should be captured and accounted for in the evaluation of the final recovery to properly assess the viability of any development plan. A typical modeling workflow accounting for geological uncertainties consists in creating a large set of 3-D geological (static) models, selecting a few representative realizations out of this set based on the calculated hydrocarbons originally in place and simulating future production from the selected reservoir models for fixed well count and locations so as to propagate the uncertainty onto the final recovery factors. However, in channelized reservoirs connectivity plays a key role in the possibility of efficiently draining the reservoir with a reasonable number of wells, thus the subset of representative realizations should be selected not only based on the hydrocarbons originally in place but also based on the connectivity among the channels. To this end, an index quantifying the channel static connectivity was defined in the literature but it is demonstrated in this paper that this index fails to account for the internal architectural layout of the reservoir, namely amalgamation, which reflects the quality of the connectivity between channels. Thus, a new index is proposed by the authors to quantify channel amalgamation and steer the selection of representative geological models for subsequent fluid flow simulations. This new index was calculated for a series of synthetic channelized 3-D static models characterized by different degrees of channel sinuosity. Each model was then dynamically simulated under the same production constraints and the final hydrocarbon recovery was obtained. Eventually, the existence of a relation between channel amalgamation and production performance was assessed to prove the validity of the proposed index as a sampling criterion. The results confirmed that channel amalgamation, more than static connectivity, affects reservoir performance thus can be a better indicator to capture reservoir uncertainty. Nonetheless, the use of a global indicator still presents limits in the description of the internal geological setting of the reservoirs and this has implications in achieving an accurate selection of a subset of equiprobable models. Only by introducing information related to the spatial distribution of amalgamation these limits could be overcome in the future.
|Titolo:||Study of reservoir production uncertainty using channel amalgamation|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||1.1 Articolo in rivista|