Distributed Strain Sensing (DSS) and Distributed Acoustic Sensing (DAS) are two emerging technologies that provide important insights into many challenging issues related to hydraulic fracturing design and operation. In particular, we highlight fracture geometry and fracture-hit inference, stage communication and perforation cluster fluid distribution. However, given the complexity associated with multiple sources of information that constitute realistic field data, its interpretation is a major challenge faced by engineers and geoscientists. In this paper, we propose a numerical modeling of DSS/DAS that is capable of incorporating the interaction phenomenon existing between hydraulic and natural fractures. The model is used in a sensitivity study varying orientation, distribution, and length of natural fractures, with the objective to assist and optimize field data interpretation in cases where such type of fracture is present.
The numerical model incorporates rock and fluid mechanics associated with the hydraulic fracturing process and computes strain fields in the medium using Displacement Discontinuity Method (DDM). DDM is a type of Boundary Element Method (BEM) that applies net pressure for hydraulic fractures and shear stress for natural fractures to specify boundary conditions. In this case, the fiber gauge length concept is incorporated deriving displacement (i.e. DDM output) in space to obtain DSS values. DAS results are estimated by the differentiation of computed DSS in time. The impact of different configurations of natural fractures on strain and strain rate is investigated by a sensitivity study in which three different parameters describing natural fractures are varied: (1) orientation angle ranging from ±20° to ±60°, (2) fracture density examining 5 to 20 natural fractures per cluster, and (3) length varying from 2.8 ft to 29.6 ft.
This study considers multiple perforation clusters and a cross-well fiber deployment with monitor and operation wells separated by a distance of 100 ft. Results indicate that we can capture typical characteristics present in field data: heart-shaped pattern from a fracture approaching the fiber, stress shadow and fracture hits. The incorporation of shear stress into the simulation generates DSS/DAS time histories that entail complexities beyond what is observed in cases where tensile stress is the unique failure mechanism considered. Intrinsic characteristics of natural fractures can be identified in waterfall plots depending on their orientation, distribution and length. Furthermore, the variation of such components has the potential to impact stress shadowing effect and consequently the generation of throughgoing fracture systems from different perforation clusters.
The model framework captures a wide range of relevant phenomenon and provides a solid foundation for generating accurate and rich synthetic data representing multiple distinct scenarios leading to interpretation optimization. Also, the development of specific packages (commercial or otherwise) that explicitly model both DSS and DAS, incorporating the impact of fracture opening and slippage on strain and strain rate, is still in its infancy. This paper is novel in this regard and opens up new avenues of research and applications of synthetic DAS/DSS in hydraulic fracturing processes.
