ESG continues to lead the unconventional oil and gas industry in new developments for advanced microseismic analysis for hydraulic fracturing and reservoir stimulation. Paramount to this analysis is ESG's Enhanced Reservoir Characterization service - which uses advanced microseismic techniques to offer clients with unparalleled feedback on reservoir response to stimulation.
Multi-well recordings offer an opportunity to examine both fracture growth and effectiveness of pumping programs. Using patent-pending seismic moment tensor inversion (SMTI)-based approaches uniquely established by ESG and confirmed through independent assessment with university based research groups globally; information on the stress-strain field, fracture orientations, and the fracture network can be obtained. This analysis can then be used as inputs for geomechanical models, providing insight into regions of enhanced fluid flow and future production.
Enhanced Reservoir Characterization (ERC) is the culmination of nearly a decade of R&D focused on advanced microseismic analysis in unconventional reservoirs. Fundamentally, ERC aims to characterize reservoir deformation as flow through the reservoir, to understand factors like stress state, fracture complexity, and ease of reservoir deformability, and ultimately link this information to the potential for production. ERC evaluates reservoir behavior using two primary tools: ESG’s Seismic Moment Tensor Inversion (SMTI) Production Suite™ and the Flow Dynamics Suite™ using Dynamic Parameters.
With any hydraulic fracture program, it’s not enough to know where a reservoir has been stimulated or even how the fractures occurred if we can’t link this activity directly to production. Commercially available in the oil and gas industry since 2010, ESG’s patent-pending Seismic Moment Tensor Inversion (SMTI) Production Suite uses knowledge of fracture development to better understand reservoir processes, optimize completions and improve production from unconventional reservoirs.
Operators need a greater level of understanding of fluid flow within developed fracture networks to be able to predict the effectiveness of hydrocarbon delivery from stimulated zones. The Production Suite’s newest component describes hydrocarbon drainage as a result of hydraulic fracture stimulation, mapping reservoir drainage pathways within a stimulated reservoir and helping operators better predict production volumes. ESG will tailor the analysis of SMTI data to the questions of interest to the client; possible areas of analysis include:
ESG’s SMTI Production Suite™ has been validated in numerous formations across North America and the Middle East including the Horn River, Marcellus, Bakken, Barnett, Permian Basin, Granite Wash, Woodford, Montney, Duvernay, Cadomin and California Diatomite. The patent-pending workflow is based on 20 years of experience in microseismic acquisition, processing and analysis and has been successfully applied to over 200,000 moment tensor inversions to date.
The first step in advanced microseismic analysis is to calculate event source mechanisms. High quality data acquired on multiple arrays may be used to describe the mechanism of failure induced at the event source. Deliverables at this stage include fracture planes, strain axes and source types (where data quality permits).
Seismic moment tensors (SMTs) are commonly represented by the iconic “beachballs.” These representations are used to describe the orientation of fractures generated in a reservoir, and whether their mechanisms are shear, tensile opening, closures or some combination thereof.
SMTI analysis can be used to determine relative orientations, azimuth and dip of failures associated with discrete microseismic events, as well as more accurate estimates of fracture dimensions. Additionally, the degree of fracture connectivity can also be established both spatially and temporally.
Based on these analyses, the discrete fracture network can be established and utilized in reservoir models to assess the effectiveness of completions programs and potentially establish reserve levels. ESG also has developed unique geomechanical models to incorporate the DFN, SMTI values and define regions where it is expected there will be enhanced fluid flow (EFF) or an increase in enhanced permeability related to the stimulation.
Once the Discrete Fracture Network is defined, the data can be further evaluated to examine fracture complexity and intensity.
Fracture complexity (FC) is derived from the number of fracture intersections per unit volume, whereas fracture intensity (FI) is interested in the relative measure and degree of fracture length developed per unit volume. Evaluating these parameters reveals whether good connectivity exists for the analyzed stages and the degree to which effective stimulation has been achieved.
Using results of SMTI analysis of microseismic data, it is possible to develop a geomechanical-based model of fluid flow pathways and enhanced fluid flow volume within a stimulated reservoir. This approach is directly related to the relative degree of open fractures over a volume of fractures with similar orientation.
In our studies of various naturally fractured shale reservoirs in North America, we have identified that most observed failures are mixed-mode failures, typically shear-tensile with either crack opening or crack closure components of failure, and that the fractures themselves are generally related to the failure of pre-existing fractures. By examining the spatial and temporal behavior of opening dominated failures, maps of intersecting zones of potential enhanced fluid flow can be identified.
Mapping reservoir drainage pathways within a stimulated reservoir can help operators better predict production volumes. Using a gemoechanical model of strain imparted on the rock mass, we identify potential dominant flow pathways for hydrocarbon in the reservoir, providing an indication of where an dhow fast drainage will occur.
ESG has developed a new statistical approach microseismic analysis that focuses on the collective behavior of clusters of seismicity. As part of this approach, a suite of dynamic parameters were identified that combine source characteristics of microseismic events with event timing and spatial distribution to characterize, map and study the collective behavior of seismicity in a reservoir.
Examples of these dynamic parameters include Diffusion Index (direction and rate of seismic activity and associated stress transfer), Fracability Index (susceptibility of a rock mass to fracturing), Stress Index (where seismic flow is hindered by fracture complexity) and Plasticity Index (ease with which the reservoir deforms).
With these tools, ESG is helping operators better understand reservoir processes, optimize completions and improve production from unconventional reservoirs.