Novel Techniques Show Links between Reservoir Flow Directionality, Earth Stress, Fault Structure and Geomechanical Changes in Mature Waterfloods.

Abstract

Recent studies have revealed a strong correlation between the directionality of reservoir flow in waterfloods and the local orientation of horizontal earth stresses. Field applications are described of a novel technique of determining interaction between wells as an indicator of flow directionality. This technique calculates the Spearman rank correlation coefficient between flow rates at pairs of wells. These applications have demonstrated that the reservoir dynamics associated with correlated rate fluctuations have at least some component coupled to geomechanics. Coupled geomechanical-fluid flow numerical modelling is able to explain some of the observations and so offers an improved predictive tool for planning and managing waterfloods and determining optimal locations for infill wells. Introduction One of the most important parameters in designing the pattern of wells for waterflooding a reservoir is the directionality in horizontal flow; i.e. any preferred lateral direction for fluid flow across the reservoir. Recent studies have revealed a strong correlation between the directionality of reservoir fluid flow and the local orientation of modern-day maximum horizontal principal earth stress (Shmax). Even more surprisingly, this correlation holds equally well for the set of reservoirs which would not normally be described as "naturally fractured" as it does for those that obviously do contain open, conductive natural fractures. It has been conjectured that this correlation is explained by coupled processes in which the conductivities of natural fractures and faults (of which, generally speaking, there is a large population even in "unfractured" reservoirs) are altered by the geomechanical changes induced by the flooding process. According to the concepts of the metastability and self-organized criticality of the lithosphere, perturbation by even minor stress changes is likely. This conjecture was given credence by coupled numerical modelling of the geomechanical, fluid flow and heat flow processes involved in waterflooding; generic modelling of the progress of a flood front around a single injector well gave rise to similar patterns of directionality as observed in the aggregated field data. Coupled modelling therefore provides a potential new tool for improved design of waterfloods and infill drilling projects this will be further demonstrated later in this paper. Directionality The field data which allowed identification of directionality in the correlations with stress derived mainly from tracers, interference or pulse testing, or oil production response to start of nearby water injection. Communication through the reservoir has long been assessed by the strength of the response of oil production to start-up of water injection. However, in a complex schedule of well start-ups, it is often difficult to make unambiguous association between producers and injectors by this means. The technique to be described provides a more rigorous extension of this concept. Rank correlation of rates The basic technique of seeking correlation between well rates to indicate communication in the reservoir has been applied successfully in oilfields of the Former Soviet Union countries for some time.

Index system evaluating water flooding development effect of oilfield at ultra-high water cut stage

“…Because of short sequence of statistical data and different dimensions of evaluation indexes, the original data should be normalized before quantitative screening to avoid calculation error resulted from different dimensions (Heffer et al 1995). …”

The Research on the Injection Interval's Reasonable Water Injection Rate for Multi-Layer Sandstone Oilfield at Ultra-High Water Cut Stage

“…Where η w = water injection efficiency of interval, dimensionless; q wn = interval's water injection rate component to the nth connecting oil well, m 3 ; q on = replacing oil rate corresponding to q wn , m 3 .…”

“…The model can find out the curve of correlation coefficient of oil and water wells changes with time. Through calculating the correlation coefficient of water injection rate and liquid producing capacity, whether the water injection is effective or not can be judged (Heffer et al 1995). Alejandro Albertoni, Larry W Lake adopted ridge regression analysis, which declined the parameter estimation error during multiple linear regression, to obtain relatively accurate regression coefficient.…”

Research on carbonate reservoir interwell connectivity based on a modified diffusivity filter model

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