1. Equipment

Crucial to any microseismic survey is the equipment used to run the survey.  In traditional microseismic acquisitions the sensors are some type of geophones/seismometer either deployed downhole or on surface. Inherently the sensitivity and the bandwidth of the geophones have a significant role on the recorded signal quality and strength which then in turn affect the resultant microseismic attributes. Testing and maintenance of the equipment on the regular basis is also critical to ensure recording high data quality and efficient deployment.

For example, for a downhole microseismic monitoring you need to know:

• Wireline characteristics such as history, length, and strength
• Deployability of the sensor arrays based on wellbore specifications
• Whip connectors for extended interconnect (minimum 600 ft)
• Digitization at the sensor (minimum 4kHz) with continuous recording
• Different sensor types with sensitivity charts
• Intra-sensor spacing capabilities and evidence of seal integrity
• Clamping/coupling mechanism for improved vector fidelity
• Functionality in high temperature
• Tool maintenance program with evidence of post- and pre-acquisition scheduled equipment testing
• Integration capability with broadband sensors

2. Deployment

You have to make sure the vendor has the ability to deploy different configurations (multi-array, vertical, horizontal, surface) that itself depends on the region/pad in which the survey is conducted. Having a large number and successful projects in the basin wherein the frac job is conducted usually is a good sign. Ask about possible/previous deployment failures in their systems, the downtime associated with those failures, and how they resolved the issue.

3. Operations

Realtime microseismic acquisition provides you with a wealth of knowledge of the deformation caused by hydraulic fractures within the reservoir in real-time as the project is happening. So, it is important that the vendor has proven operational experience. They must be prepared for any tool/system failure that comes their way and perform smoothly under pressure. Data streaming capabilities and effective automated real-time processing is another side of this equation. At the end of the day as an operator you need to make sure you have QC metrics in place that helps you distinguish reliable from unreliable results which you received from the microseismic vendor.

4. Data Analytics and Integrated Interpretation

You want to make sure the vendor has the in-house technical competency to process the acquired data for microseismic attributes (including but not limited to location and associated errors, magnitude, stress release, energy, moment tensor solutions) and provides you with QC statistics so you know what part of the data can be trusted and used in the advanced analytics and integrated interpretation workflows.

The vendor shall have the ability to slice and dice the data and provide you with insights that are applicable to your project and worth your investment (time and budget). The larger number of projects the vendor had in the target Basin/Formation is valuable as they will be able to provide you with collective insight before and after project completion. Making sure you will be provided with information that are relevant and actionable in a timely manner is very important.

Don’t settle for data dumps.

Ted Urbancic, Scientific Advisor

If you need more details on any of the qualifiers discussed in this article contact us, we would be more than happy to help. Subscribe to our mailing list for more technical tips and tricks.

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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.

The post Microseismicity-derived fracture network characterization of unconventional reservoirs by topology appeared first on Meta | Innovative AI Analytics and Training Software.

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.

The post Integration of SMTI topology with dynamic parameter analysis to characterize fracture-connectivity related to flow and production along wellbores in the STACK play appeared first on Meta | Innovative AI Analytics and Training Software.