Diagnosing Multistage Fracture Treatments with Distributed Fiber-Optic Sensors
- Iuliia Pakhotina (Texas A&M University) | Shohei Sakaida (Texas A&M University) | Ding Zhu (Texas A&M University) | A. Daniel Hill (Texas A&M University)
- Document ID
- Society of Petroleum Engineers
- SPE Hydraulic Fracturing Technology Conference and Exhibition, 4-6 February, The Woodlands, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2020. Society of Petroleum Engineers
- fracture diagnosis, distributed acoustic sensing, distributed temperature sensing
- 362 in the last 30 days
- 367 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
Distributed acoustic sensing technology is a diagnostic method that has been implemented in the oil and gas industry for flow monitoring during injection or production. One of the applications is to estimate fluid distribution during hydraulic fracturing treatment. This is an invaluable diagnostic tool for multistage fracture treatments because of the large number of parameters and high uncertainty involved in these fracture treatments. Distributed acoustic sensor (DAS) measurements are based on data extracted from a fiber optic cable installed in a wellbore. Fiber optic cable strain is sensitive to temperature and acoustic variations induced by fluid flow with different fluid properties and fracture geometries. These parameters are evaluated from the back-scattered laser pulse through the fiber using coherent Rayleigh backscattering for DAS and Raman backscattering for distributed temperature sensing (DTS). The DAS interrogation system acquires strain response to acoustic variations along the measured depth of the wellbore for all periods of time.
This study presents a method of interpretation of flow rate distribution from acoustic signals from DAS measurements. Raw acoustic measurements are transformed to energy attribute distribution for all necessary depth locations and timeframe. It allows to calculate energy for each perforation cluster location. This calculation demands proper depth interval consideration for each perforation cluster. Local minimums of time average energy attribute allow to find depth window where integrate DAS channels measurements for each time step occurs. Based on the previous experimental and computational fluid dynamic investigations, the correlation between acoustic signal and flow rate is applied to interpret the measured DAS data to flow distribution.
In this paper, the system of equations which connects acoustic energy response with clusters flow rate distribution during the injection period using these correlations is introduced. The solution of this system allows to calculate cumulative volume for each perforation cluster on each time step and in the end of fracture treatment. As additional verification of flow rate distribution, the results of DAS interpretation were compared with interpretation results of DTS. A field example is used to illustrate the interpretation procedure.
From this work, it is concluded that besides qualitative analysis, the DAS interpretation method provides a quantitative estimation of flow distribution. Based on the current assumptions, the interpretation results from DAS and DTS are comparable with satisfactory agreement. The combined DAS and DTS interpretations help to understand cluster efficiency in multistage fracture treatments.
|File Size||1 MB||Number of Pages||19|
Amini, S., Kavousi, P., & Carr, T. R. (2017, July 24). Application of Fiber-optic Temperature Data Analysis in Hydraulic Fracturing Evaluation: A Case Study in Marcellus Shale. Unconventional Resources Technology Conference. https://doi.org/10.15530/URTEC-2017-2686732
Chen, K., Zhu, D., & Hill, A. D. (2015, September 28). Acoustic Signature of Flow From a Fractured Wellbore. Society of Petroleum Engineers. https://doi.org/10.2118/174877-MS
David A. Krohn, Trevor W. MacDougall, Alexis Mendez (2015) Fiber Optic Sensors: Fundamentals and Applications, Fourth Edition. https://doi-org.srv-proxy1.library.tamu.edu/10.1117/3.1002910
Kavousi, P., Carr, T., Wilson, T., Amini, S., Wilson, C., Thomas, M., MacPhail, K., Crandall, D., Carney, BJ, Costello, I., Hewitt, J. (2017, October 23). Correlating distributed acoustic sensing (DAS) to natural fracture intensity for the Marcellus Shale. Society of Exploration Geophysicists. https://doi.org/10.1190/segam2017-17675576.1
La Follett, J., Wyker, B., Hemink, G., Hornman, K., Lumens, P., & Franzen, A. (2014, October 29). Evaluation of Fiber-Optic Cables for use in Distributed Acoustic Sensing: Commercially Available Cables and Novel Cable Designs. Society of Exploration Geophysicists. http://dx.doi.org/10.1190/segam2014-0297.1
Molenaar, M. M., Hill, D., Webster, P., Fidan, E., & Birch, B. (2011, January 1). First Downhole Application of Distributed Acoustic Sensing (DAS) for Hydraulic Fracturing Monitoring and Diagnostics. Society of Petroleum Engineers. https://doi.org/10.2118/140561-MS
Molenaar, M. M., Fidan, E., & Hill, D. (2012, January 1). Real-Time Downhole Monitoring Of Hydraulic Fracturing Treatments Using Fibre Optic Distributed Temperature And Acoustic Sensing. Society of Petroleum Engineers. https://doi.org/10.2118/152981-MS
Oliver, D.S., Reynolds, A.C., and Liu, N.. 2008. Theory for Petroleum Reservoir Characterization and History Matching. Cambridge, UK: Cambridge University Press. https://doi.org/10.1017/CBO9780511535642
Pakhotina, J., Zhu, D., Hill, A. D., & Santos, R. (2017, October 9). Characterization of Production through a Fracture Cell Using Acoustic Data. Society of Petroleum Engineers. https://doi.org/10.2118/187357-MS
Shirdel, M., Buell, R. S., Wells, M., Muharam, C., & Sims, J. (2016, September 26). Horizontal Steam Injection Flow Profiling Using Fiber Optics. Society of Petroleum Engineers. https://doi.org/10.2118/181431-MS
Soodak, C., Gould, G., & McBee, L. (1985, January 1). A Fiber Optic Logging Cable System. Offshore Technology Conference. https://doi.org/10.4043/4977-MS
Ugueto, G. A., Ehiwario, M., Grae, A., Molenaar, M., Mccoy, K., Huckabee, P., & Barree, B. (2014, February 4). Application of Integrated Advanced Diagnostics and Modeling To Improve Hydraulic Fracture Stimulation Analysis and Optimization. Society of Petroleum Engineers. https://doi.org/10.2118/168603-MS
Willis, M. E., Ellmauthaler, A., LeBlanc, M., Palacios, W., & Wu, X. (2018, November 30). Comparing distributed acoustic sensing, vertical seismic profile data acquired with single- and multi-mode fiber optic cables. Society of Exploration Geophysicists. https://doi.org/10.1190/segam2018-2996212.1
Worsley, J., Minto, C., Hill, D., Godfrey, A., & Ashdown, J. (2014, November 10). Fibre Optic Four Mode Leak Detection for Gas, Liquids and Multiphase Products. Society of Petroleum Engineers. https://doi.org/10.2118/171824-MS
Yoshida, N., Hill, A.D., & Zhu, D. (2018, October 1). Comprehensive Modeling of Downhole Temperature in a Horizontal Well with Multiple Fractures. Society of Petroleum Engineers. https://doi.org/10.2118/181812-PA
Yoshioka, K., Zhu, D., Hill, A.D., Dawkrajai, P. and Lake, L.W. 2005. A Comprehensive Model of Temperature Behavior in a Horizontal Well. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, USA, 9-12 October. SPE-95656-MS. https://doi.org/10.2118/95656-MS.
Zhang, S., & Zhu, D. (2019, March 1). Efficient Flow Rate Profiling for Multiphase Flow in Horizontal Wells Using Downhole Temperature Measurement. International Petroleum Technology Conference. https://doi.org/10.2523/IPTC-19138-MS