Determination of Proppant and Fluid Schedules From Fracturing-Pressure Decline

TLDR

Exposure is critical for selecting fluid additives in large, high‑temperature fracturing treatments. The authors present a procedure for designing fracture treatments when little or no prior information is available. The procedure relies on fluid efficiency—fracture volume divided by injected fluid volume—which is estimated from a pressure‑decline analysis of a calibration treatment, requiring an assumption about the cooled portion of the fracture face and allowing predictions of efficiency, width, and penetration when the calibration is smaller than the actual stimulation. Fluid efficiency alone determines pad size and optimal proppant schedule without needing a fracture‑geometry model, also predicts fluid exposure time, and, when a geometry model is assumed, the decline analysis yields fluid‑loss coefficient, fracture width, and penetration.

Abstract

Summary A procedure is presented for designing a fracture treatment when little or no information is available. This procedure is based on fluid efficiency, which is defined as the fracture volume divided by the injected fluid volume. The fluid efficiency for a treatment was found to determine the pad size and optimum proppant schedule completely without any assumption of the appropriate fracture-geometry model or associated parameters. The efficiency was also found to determine the fluid's exposure time to temperature. This determination requires an assumption for the portion of the fracture face that is cooled during a treatment. The exposure is important for defining the fluid additives of relatively large and high-temperature treatments. The fluid efficiency can be determined from a pressure-decline analysis for a calibration treatment performed before the actual stimulation treatment. In addition, if the appropriate geometry model is assumed, the decline analysis of the calibration treatment provides inferred values of fluid-loss coefficient and fracture width and penetration. Also, for the case when the calibration treatment is smaller than the actual stimulation, analyses are presented for predicting the relative change in efficiency, width, and penetration for the treatments.