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Integration of SMTI topology with dynamic parameter analysis to characterize fracture connectivity related to flow and production along wellbores in the STACK playNormal access

Authors: Adam M. Baig, Ellie P. Ardakani, Ted Urbancic, Dan Kahn, Jamie Rich, David Langton and Ken Silver
Journal name: First Break
Issue: Vol 35, No 12, December 2017 pp. 59 - 66
Language: English
Info: Article, PDF ( 747.9Kb )
Price: € 30

A number of years ago, there was an appeal to microseismic service providers and end users to go ‘beyond the dots’ in terms of the types of analysis that can be performed to relate the microseismic waveforms to problems in terms of drilling, completion, and field development. While this call to arms has often been interpreted rather specifically, in terms of moment tensor inversion, this is just one aspect of how microseismic data can be looked at beyond the rather limited information afforded to by their locations. Even in terms of determining the moment tensors of microseismic events, the question of how to use this information to affect business decisions is not intuitively obvious. In this paper, we describe a number of analyses that aim to make use of microseismic data, from moment tensors to other source parameters, in the context of a completion in the STACK play in Kingfisher County, Oklahoma. Key to extracting information from these data is the concept that a single microseismic event does not afford a lot of information in of itself. The critical idea is that it is the interaction of different microseismic events which captures processes that are not elucidated in the consideration of events individually. 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.

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