We have developed a unique approach to understand the influence of fractures on fluid flow and production from impermeable reservoirs and evaluate completion effectiveness. We characterize the microseismicity-derived discrete fracture network in a North American shale-gas reservoir using modified scanline and topology methods. Using concepts of node and branch classification and assessing the number of connections (fracture intersections), the network connectivity is established volumetrically. The zones of permeability enhancement are then identified using the connection per branch and line (CB and CL), tied to percolation thresholds of the fracture system. These zones consist of a primary zone with a high proportion of doubly connected fractures, a secondary zone populated with partially connected fractures, and a tertiary or unstimulated zone dominated by isolated fractures. These divisions are reflected in the deformation that is observed in the reservoir as measured through a cluster-based description of the microseismicity. The primary and secondary zones are considered spanning fracture clusters, and they take part in production, whereas the tertiary zone is recognized as nonspanning fractures, and though it may enhance the bulk permeability of the rock mass, it is unlikely to contribute to reservoir production.

Check out our full article published in SEG Interpretation Journal, Volume 6, Issue 2 or contact us to get a copy.

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While event distributions tend to be the first and most frequently examined aspect of a microseismic monitoring effort, because the generation of a microseismic event is not immediately diagnostic of fluid-induced fracturing, the event clouds tend to overestimate the effective area of fracturing. In order to gain further insight into how microseismic events describe effective fracture growth, a deeper look at the waveforms through techniques like Seismic Moment Tensor Inversion (SMTI) and subsequent stress inversion can be effective. These steps are necessary to describe the discrete network of cracks, from the microseismic data. Using a fracture network topology approach, the network can then be characterized in terms of its ability to percolate fluids.

We compare how cracks behave for a regular geometric shot cluster (GSC) and a variable shot cluster (VSC) and assess variations in the stimulations. Both shot clusters were completed in consecutive stages of the same lateral. The mechanisms from the GSC stages show shear-dominant mechanisms with opening and closing components in roughly equal proportions, while the VSC stages have a higher concentration of shear-tensile opening failures. Furthermore, the GSC stages showed modest connectivity around the treatment well relative to the VSC stages, which showed significant growth of connected fractures away from the treatment well. Since the VSC stages also showed relatively more stable stress behaviour than the GSC stages, these observations suggest that stability in stresses allows for steady growth of the fracture network across the reservoir.

This type of higher-order analysis of microseismic data is critical to establishing value from this data stream in terms of completion evaluation. The recognition that each microseismic event is tied to the rupture of a crack in the reservoir allows for these types of comparisons to be made in a robust fashion and be tied to the underlying geomechanics that governs the type of response from one type of completion to the other.

Check out our full article published in SPE (Hydraulic Fracturing Technology Conference 2018) or contact us to get a copy.

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Using the example of seismic moment tensor inversion (SMTI) data, we describe an approach for obtaining a picture of a connected fracture network that can further be described in terms of the percolation properties of the network. This allows for the moment tensor data to be linked to where the hydraulic stimulation fractures connect to the treatment well and therefore the volumes where we may expect production.
Further consideration of microseismic event clusters can identify the different deformation processes that accompany the microseismicity. By clustering events of similar character, and considering both how they are distributed in time and space, as well as the insights into their failure processes from a detailed study of their source mechanics, the deformation in the reservoir
can be mapped. Characterizing the deformation by the degree of co-seismic (anelastic) deformation allows the processes in the reservoir to be described in terms of different deformation indexes, ‘dynamic parameters’: plasticity index (PI) corresponding to anelastic deformation; stress index (SI) as related to the localized stress behaviour/conditions leading to seismicity; and diffusion index (DI) which describes the rate of stress transfer as it results in seismicity throughout the volume of interest.

We introduce the site and give an overview to the microseimsic data acquisition for a lateral well completion in the STACK play (Sooner Trend Anadarko basin Canadian and Kingfisher counties). We then describe an approach for processing these data, through moment tensor inversion, into a picture of the Discrete Fracture Network (DFN). This requires a methodology to group events occurring under like stress conditions to invert for the stress ratio and the principal stress axes, such that the fracture planes may be deterministically derived from the moment tensor data. We also discuss the methodology to determine the cluster-based dynamic parameters. We then illustrate how we can use these tools to arrive at an integrated interpretation of processes occurring during the hydraulic completion, and how these data can be used to affect design decisions for completion and field development.

Check out our full article published in EAGE First Break, Volume 35, Number 12, or contact us to get a copy.

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