Our services
Simulation services to maximize return on investment
Turnkey fracture design and reservoir simulation services
Close collaboration
We work closely with clients to align on priorities and support business objectives. We've refined the process over dozens of projects across North and South America.
Understand the why
We don’t just hand you a solution. We help you understand the approach, think critically about simulation inputs, and explain what is happening in the reservoir and why.
Build your capabilities
We strive to transfer our knowledge so you can apply it to future well designs and projects.
Our hydraulic fracturing and reservoir simulation solutions apply to a broad range of applications
Mitigate parent-child problems
Reduce production loss when drilling infill wells.
Enhanced oil recovery in shale
Increase recovery factor by 2-3x.
Well spacing optimization
Optimize the distance between wells to maximize capital efficiency.
Landing depth optimization
Maximize reservoir contact and optimize well spacing in 3D.
Fracturing design optimization
Customize frac design to your formation and economic drivers.
Geothermal systems
Simulate hydraulic stimulation and long-term circulation in a single integrated model.
The process
Following the right modeling workflow is critical for a successful project. Every ResFrac project includes a series of ‘checkpoint’ meetings at key junctures to keep stakeholders aligned and ensure strong engineering design principles.
Model construction and setup
Ingest data, set up an initial model, and present back to confirm everything has been communicated successfully.
Model calibration
Determine ‘key observations’ to be matched from field data. Plan the calibration process in advance. Then, vary parameters to achieve a match.
Design optimization
Align on the design variables to optimize. Perform a quantitative optimization for NPV, investment efficiency, or any other objective.
Design field implementation
Establish baseline performance expectations. Establish performance metrics, and try to minimize uncontrolled variables.
Field implementation
Evaluate results
Compare actual production with predicted. What are the ‘key observations’ from the field data? How do they align with expectation? If there is variance, what are potential causes? Are there additional design changes to consider next?
Recent content from the ResFrac blog
Proppant distribution between perforation clusters
his blog post summarizes the model for calculating proppant distribution between perforation clusters. A very detailed description of the model and literature review are available in [1]. The purpose here is to outline the model and its main features, to demonstrate the comparison with some of the available data (more comparisons in [1]), as well as to discuss limiting cases and sensitivities to various parameters. This blog post is solely focused on presenting the mathematical model. In future work, the results will be applied to practical optimization decisions.
Simulating ‘Fractal Fracture Swarms’ in a General-Purpose Reservoir Simulator
This blog post describes a new capability in ResFrac to capture the effect of ‘fracture swarms’ on production decline trends. Based on work from Acuna (2020), the idea is that variable spacing between fractures causes a gradual onset of production interference. Fractures in a swarm may be numerous and tightly spaced, so rather than representing each individual crack in the model, we treat each swarm as a single crack and use a numerical technique to capture their effects. In ResFrac, this capability is useful because it provides another mechanism for explaining (and matching) production drawdown trends. For further details, refer to Section 19.10 from McClure et al. (2022).
How to Diagnose False Radial Flow in a Diagnostic Fracture Injection Test (DFIT)
Genuine radial flow is rare in shale DFITs. If it does occur, it is typically observed in tests with very low injection volume (less than 10-20 bbl), unusually long shut-in (longer than one week), and relatively high permeability (greater than one microdarcy). Genuine radial flow should only be diagnosed if it occurs after an extended (at least one log cycle) period of after-closure linear flow. If ‘false radial’ flow is misdiagnosed and used to estimate permeability, it leads to a large overestimate (10-100x).
