Abstract

Since the onset of unconventional reservoir development, multi-fractured horizontal wells have been the preferred method for exploitation. Now that the practice has been established, the next question is how to develop the acreage position optimally. As suggested by Ramos-Peon et. al., 2020, optimal well spacing continues to be one of the major topics of debate in the development of unconventional hydrocarbon plays. There remains a lack of unified approach among operators with respect to the choice of an ideal development strategy. Well spacing is the product of optimizing many parameters - one of the most important being the impact of well interference on the estimated ultimate recovery (EUR) per well, when more than one well is drilled per drilling spacing unit (DSU).

This paper outlines the implementation of three multi-disciplinary methods and best practices that when used in conjunction, will reduce uncertainty on the expected EUR and converge on a number within a range that can be used to calculate economic metrics specific to the operator; the most common ones being rate of return (ROR) and net present value (NPV). The first method is based on a fit-for-purpose experiential and semi-analytical model where certain parameters such as ultimate recovery per section, recovery per well, recovery per well as the well count approaches a significantly large number, and the way the decline is expected to behave are established by empirical parameters. The EUR when no interference exists is calculated by rate transient analysis (RTA) and validated by interior/exterior well analysis using geometric EUR calculations. The second method borrows the recovery factor technique for conventional reservoirs and finally the third method uses unbiased machine learning forecasting at a basin level to eliminate human bias when forecasting EURs.

Using these methods in combination with deliberate selection of interior (fully bound by offset producers) wells, has proven successful where at least one parent well and varying spacing tests are available. When tied to recovery factor and unbiased forecasting, the interference degradation curve discussed in this paper has aided in increasing accuracy of EUR forecasting for wells affected by interference due to well spacing, independently if the spacing test has been carried in a single or multi-bench scheme.

Given the complexity of unconventional plays and the continuous evolution of understanding their performance, a fast and efficient workflow that encompasses a combination of prove technologies is presented in this paper. This workflow provides a powerful early asset development tool meant to align expected performance while keeping bias in check.

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