Statistical reservoir model based on detected flow events

摘要

Computerized method and system for deriving a statistical reservoir model of associations between injecting wells and producing wells. Potential injector events are interactively identified from time series measurement data of flow rates at the wells, with confirmation that some response to those injector events appears at producing wells. Gradient analysis is applied to cumulative production time series of the producing wells, to identify points in time at which the gradient of cumulative production changes by more than a threshold value. The identified potential producer events are spread in time and again thresholded. An automated association program rank orders injector-producer associations according to strength of the association. A capacitance-resistivity reservoir model is evaluated, using the flow rate measurement data, for the highest-ranked injector-producer associations. Additional associations are added to subsequent iterations of the reservoir model, until improvement in the uncertainty in the evaluated model parameters is not statistically significant.

主权项

1. A computer-implemented method of evaluating waterflood injection at a subsurface hydrocarbon reservoir into which one or more producing wells and one or more injecting wells have been drilled, comprising:
receiving measurement data over time corresponding to flow rates at one or more producing wells and one or more injecting wells; from the received measurement data, identifying a plurality of associations between one of the producing wells and one of the injecting wells, based on time correspondence of events at the one of the injecting well and events at the one of the production wells identified in the received measurement data; each of the identified associations having a measure of strength of association; ordering the identified associations according to a rank of the strength of association; applying one or more of the associations with the highest ranks to a capacitance-resistivity reservoir model; evaluating, by a processor, the capacitance-resistivity reservoir model relative to the measurement data to derive a set of model parameters and an associated uncertainty statistic; applying a next one or more of the associations, selected according to the ordering of the associations by rank, to the capacitance-resistivity reservoir model; evaluating, by the processor, the capacitance-resistivity reservoir model, with the applied next one or more of the associations, relative to the measurement data, to derive a set of model parameters and an associated uncertainty statistic; repeating the applying a next one or more of the associations and evaluating the capacitance-resistivity reservoir model with the applied next one or more of the associations, until the uncertainty statistic reflects similarity of the model parameters from the most recent evaluating and the model parameters from a prior evaluating, to a selected statistical significance; and changing fluid injection flow in one of the injecting wells based on analysis of the capacitance-resistivity reservoir model.