In-Well Fracking Monitoring

Permanently installed fiber optics in injection wells capture continuous data on strain and temperature, tracking fluid and proppant movements during hydraulic treatments.

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Reliable & Innovative In-Well Fracking Monitoring

Permanently installed fiber in and injection well can acquire continuous broadband strain and temperature variations along the entire length of the wellbore associated with fluid and proppant movement during hydraulic treatments. Often, both Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) are used simultaneously to better evaluate the efficiency of different treatment designs, mitigate risk associated costs, and ultimately ensure that capital is being placed as planned. 

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Diagnose and Optimize Fracture Treatments

Our in-well monitoring solutions provides information on:

  • Cluster level efficiency – Determine if fluid and proppants are evenly distributed across the target clusters
  • Fracture identification – Where and when fractures initiate during treatment
  • Evaluation of diversion techniques
  • Stage isolation – Bridge plug failure and compromised well integrity
Evaluation

Distributed Acoustic Sensing

DAS measures the fluid flow at individual perforation clusters during treatment (left), enabling computation of fluid and proppant distributions (right).

During hydraulic treatments, DAS essentially acts as a noise log by measuring the movement of fluid and proppants inside the wellbore and exiting through perforation clusters (PC). Critical information on additional in-well variations can be described, such as perforation gun locations, the timing of ball seat placement, sand plugging/bridging, and unwanted fluid communication between stages.

Using the spectral noise model, we can associate the DAS acoustic response with the flow rate of fluid and proppants passing through perforation clusters during hydraulic treatment. This enables us to provide quantitative volumetric distribution estimates at the PC level, providing crucial information on treatment design efficiencies.

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Distributed Temperature Sensing

Distributed Temperature Sensing (DTS) measures the temperature variations associated with the movement of relatively cooler fracking fluid within the wellbore. Through our DTS interpretations we can identify and locate in-well variations such as compromised lateral cement quality, interstage fluid communication from failed or ill configured plugs, and oil and gas production logging. Additionally, the integration of DAS and DTS can be used to identify the mechanisms behind interstage fluid communication and the time evolution of fluid distribution during a fracking stage.

DTS monitoring enables the detection of fluid communication between adjacent stages: (left) displays the temperature variations for several treatment stages. (right) zoomed in view of a stage where cooling is observed beyond the bridge plug depth due to possible plug failure.

Evaluation

Understanding Hydraulic Fracturing Performance

The Uniformity Index is a single quantitative value that describes the “evenness” of fluid and proppant distribution across the perforation clusters within the targeted treatment interval. 

Our in-well monitoring service offers vital qualitative and quantitative insights at the perforation level. This guides operators with:

  • Evaluating completion design performance, adjusting as needed for efficient fluid and proppant distribution.
  • Pinpointing over/under stimulated zones for precise oil and gas production model calibration.
  • Identifying and mitigating risks associated with in-well variations, such as ill configured engineering parameters for cement, casing, and plug designs.

What Can We Gain From This Analysis?

  • Enhanced Completion Designs

    Optimize completion designs by integrating detailed fluid and proppant distribution data.

  • Risk Mitigation

    Identify and mitigate risks associated with well integrity and stage isolation failures.

  • Improved Production Models

    Calibrate oil and gas production models by pinpointing over/under stimulated zones.

  • Operational Efficiency

    Increase operational efficiency by evaluating and fine-tuning diversion techniques and treatment parameters.