Let’s start with some fundamentals. Hydraulic fracturing is accomplished through initiating a weakness point (or several) around a well. One approach commonly used is through the use of a perforation gun, and then pumping high pressure fluids and particulates (proppant) though the well at these entry points (commonly referred to as perfs or perf zones) extend into hydraulic fractures away from the treatment well. These hydraulic fractures will interact with the pre-existing network or fractures in the medium, and will generate a slip on these fractures. The zone of “influence” of the stimulation can be potentially outlined based on the observed fracturing that occurs under dynamic stress conditions.

Stimulated Reservoir Volume (SRV)

If the SRV can be estimated accurately from microseismicity, then the operators can predict how much hydrocarbon they may produce with time and gain accurate estimates of Net Present Value (NPV) after hydraulic fracturing. Other information form other data streams are integrated with the estimated SRV at this step. Beyond the economics of the production size, understanding how far away from the well primary production may be expected, and along what azimuth, informs an operator on how to drill their child wells to complete their asset.

The Holy Grail

A production engineer will usually assume that primary production (that is, the early production that comes through the well with the highest rate) is dominated by the cracks that have received proppant, so called “propped volume.” The “holy grail” of microseismic monitoring of hydraulic fractures is therefore to determine which events represent fractures that will receive proppant from the other cloud of events. While mapping proppant distribution is a lofty aspiration, a useful lower-hanging fruit is to determine events that are showing more connectivity in close proximity to the treatment well, which are more likely fluid influenced fractures versus other that are stress induced. By focusing on these fluid-connected areas, plausible volumes of production can be obtained, resulting in better estimates for SRV.

Above is the “Completion Evaluator” simulation hosted on the metaKinetic platform. Using this application you can explore activated fractures identified through microseismic distribution, and examine inferred modes of failure and dynamics of stress/strain field, and witness their relationship to treatment parameters such as pressure, slurry rate, and proppant concentration.

Beyond Accurate SRV Estimates

Fracturing and stress behavior are paramount to understanding the effectiveness of stimulation programs. As differences in injection rates, pressure, and fluid and proppant types occur during a stimulation, the rock fracturing response is directly related to the dynamic stress conditions that make it ideal for different fracture sets to be activated. Tracking fracture orientations, failure types, and localized stress orientations provides the impetus for defining the roles of different injection parameters. 

The microseismic response of different treatments may be used to understand how to effectively stimulate a reservoir, and adjust the stimulation parameters based on the reservoir response. Further to the optimization of stimulation parameters, optimally all the fluid and proppant will be contained within “zone”, the targeted hydrocarbon-bearing lithological formation. Sparse events out of zone are often not indicative of fractures that are connected to producing region. 

Microseismicity, if well located and characterized, can outline the effectively stimulated regions, and can therefore be used to adjust the stimulations to avoid out-of-zone growth. The discrimination of regions that have not been effectively stimulated within zones of stimulation – the so-called “bypass” zones – can be identified as areas of relative quiescence. Once identified, these regions can be targeted with further development of the asset.  

Ted Urbancic, Scientific Advisor

Want access to this simulation and more on the metaKinetic platform? Contact us!

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The main difference between “Surface MS Monitoring”, “Downhole MS Monitoring”, and “DAS MS Monitoring” goes back to the sensitivity and the frequency band of the instrumentation used for monitoring.

Conventional Surface vs. Downhole MS Monitoring

First let’s compare the Surface vs. Downhole MS Monitoring using 3C geophones (call it conventional): Although surface MS processing (mainly via stacking and migration) is often quicker than downhole data processing (first break picking), the downhole monitoring geophones (usually 15 Hz) provides a wider range of detectability in the reservoir since they resolve smaller size events. However, the 15 Hz geophones are unable to give accurate magnitude estimates for larger events (> Mw -1) due to saturation. That’s where the surface MS acquisition comes in handy using broadband geophones with main frequency cutoff as low as 0.01 Hz that can pick up very low frequency events (> Mw -1 and above).   

Conventional Downhole vs. DAS MS Monitoring

In the case of DAS MS monitoring, since the sensitivity of fiber is lower than downhole geophones the acquired dataset is usually sparse (i.e., fewer events are detected), therefore it provides less information about the dynamic reservoir behavior through advanced analytics. To improve sensitivity, signals from multiple points along the fiber can be stacked but this results in a decrease in MS location accuracy. Using DAS for MS is also restrictive in determining characteristics of the microseismic events. Despite the charm of simpler deployment of Fiber for hydraulic fracturing, more R&D work is needed for this technique to arrive at scientific maturity for MS monitoring.

Combining Monitoring Methods

The downhole monitoring for hydraulic fracturing always wins if you have to choose one method over another (conditional to creating appropriate coverage). If you are combining Surface MS and DAS MS monitoring, you should know that both these techniques will provide you with a dataset that is biased toward larger magnitude events occurring closer to the treatment wells because that’s what the instruments are capable of resolving. Meanwhile, the Surface MS Monitoring is complementary to conventional Downhole since the surface network extends the recording range of seismicity generated during a stimulation. The cost of adding a sparse surface network is generally minimal and is something that should be considered for many plays.

If you are in a decision-making position, budgeting for DAS and MS surveys, you need to take as many details as possible into consideration to arrive at the monitoring solution that works best for your asset. Don’t underestimate the value of feasibility studies (modeling) before you make a monitoring service purchase decision to reduce the unexpected surprises with the acquired MS data.

Ellie Ardakani, CEO @ Meta

Above you are visualizing such modeling using 5 surface sensors in the metaKinetic platform.

For sure there are more aspects into these techniques that must be considered. Want to have access to this simulation and explore by yourself or have further questions? Contact us!

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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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Check out our expanded abstract published by SEG (Technical Program 2018) or contact us to get a copy.

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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.

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Check out the expanded abstract published by CSEG (Geoconvention 2018) or contact us to get a copy.

The post Investigation of the impact of depleted zones and completion sequence on hydraulic fracturing performance using microseismic collective behaviour analysis appeared first on Meta | Innovative AI Analytics and Training Software.

Effective hydraulic fracturing in unconventional shale reservoirs requires an understanding of the pre-existing discontinuities (impermeable/not effectively connected natural fractures) state and an assessment of whether at any point of the stimulation it is energetically favourable to move fluids within the reservoir. The dynamic nature of the local stress regime owing to hydraulic fracturing leads to stimulation of different fracture sets which could include bedding-parallel fractures and bedding planes. Describing the progression of the fracturing into the formation and ancillary issues of how far into the reservoir the rock has been stimulated and the stimulation containment provides the opportunity for operators to potentially control fracture behaviour and improve completion designs.

Evaluation of hydraulic fracturing generated microseismicity through seismic moment tensor inversion and further stress inversion techniques, where there is high signal-to-noise signals registered with a sufficient angular distribution of sensors around the events, can resolve the orientations of the fractures on which these ruptures occur. This process then identifies the predominance of fracture types, fracture orientations and dimensions within the stimulated reservoir.

The comparison of fracture network associated with a stimulation of different stages we can establish the importance of different fracture sets in effectively constraining the stimulation to the zone of interest. This information further allows operators to establish the stimulation effectiveness if production data is available.

Check out our full article published in First Break Journal Vol 35, No 4, April 2017 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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We connect these concepts of fluid-driven vs stress-triggered seismicity to volumes in the reservoir of different percolation potentials. Fluid-driven processes are of primary importance to tying the microseismicity to productive volume, but we suggest that the stress-induced processes may also play a significant role in identifying poorly- or well-connected crack networks and hence the stimulated volumes within the reservoir. As such, we can resolve the likely volumes of primary (initial) and secondary (longer-term) production through these clustering processes and ensuring the behaviors determined are consistent with more of a fluid-induced vs stress-triggered behavior. This ranking of volumes in terms of productivity is analogous to work done in predicting variations in enhanced permeability in different engineering workflows, with the added benefit of being able to show variability along the well. As such, we suggest that coupling the dynamic parameter response to estimating and ranking the geometries of volumes of different productivity provides a rigorous methodology to tie microseismicity to stimulated reservoir volume, allowing for credible predictions of accessible reserves to be made over a short timescale.

Check out our full article published by Unconventional Resources Technology Conference (URTEC-2697672-MS) or contact us to get a copy.

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