This work presents the methodology of using the "rate-integral" (i.e., cumulative production/time) to assist with "time-rate" well performance analysis or "Decline Curve Analysis" (DCA) for multi-fractured horizontal wells (MFHW). This work provides a methodology for cases where poor data quality make unique analyses/interpretations difficult for decline curve analyses (DCA).
Our primary objectives are as follows:
- Introduce the "qDb-Rate Integral" plot to assist with "time-rate" data analysis/interpretation.
- Derive the time-rate-integral form of current and evolving decline curve analysis models
- Derive the auxiliary diagnostic plotting functions (i.e., D(t) and b(t) parameters) in time-rate-integral space.
- Validate the methodology using simulated unconventional "time-rate" data.
- Provide a systemic and comprehensive demonstration of the rate-integral methodology to field data.
In this work, the primary goal of using the "rate-integral" methodology is to improve the traditional time-rate production diagnostics for the following applications:
- The analysis/interpretation of noisy and/or inconsistent "time-rate" data.
- The prediction of the Arps' b-parameter.
- The calculation and use of derivative-based diagnostic plotting functions (i.e., D(t) and b(t)).
The time-rate-integral approach is not intended to replace traditional production diagnostic and analysis methods, but rather be used as a compliment. This methodology allows for the "smoothing" of "time-rate" data without the introduction of an external smoothing mechanism — we just employ cumulative production functions. The smoother "time-rate integral" data should provide more consistent analyses and diagnostic interpretations.
In terms of deliverables, this work provides:
- The derivation of "time-rate-integral" models and auxiliary diagnostic plotting functions for:
-- The modified hyperbolic DCA relation.
-- The power-law exponential DCA relation.
- Guidance on the use of the "rate-integral" methodology as a complement to traditional DCA analysis.
- "Conceptual" validation of the "rate-integral" methodology using synthetic data.
- Numerous "demonstration" field data examples with comment and guidance.
Although counterintuitive in 2021, one of the major issues facing the oil and gas industry today is data quality. The "time-rate" data acquired from a "typical" unconventional well are often quite erratic (typically due to onsite and offset operational activities). Errors and noise in data are magnified when using a numerical differentiation method [e.g., Bourdet (1989)], for the instantaneous calculation of the loss-ratio [1/D(t)] and loss-ratio derivative [b(t)], which are required for modern DCA diagnostic analyses and interpretations. Using the rate-integral approach, coupled with the proposed "qDb-Rate Integral" plot enables more consistent decline curve analyses to be performed in instances of poor "time-rate" data quality. However; this method should also significantly improve the general task of decline curve analyses, and may be a better approach for the "data analytics" methodologies currently being proposed for decline curve analyses for wells in unconventional reservoirs.