Case Studies: Optimizing BHA Performance by Leveraging Data and Advanced Modeling
- Mojtaba Shahri (Apache Corp.) | Moisan James (Apache Corp.) | Alan Vasicek (Apache Corp.) | Roy De Napoli (Apache Corp.) | Matthew White (Apache Corp.) | Michael Behounek (Apache Corp.) | John D'Angelo (University of Texas at Austin) | Pradeep Ashok (University of Texas at Austin) | Eric van Oort (University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Tortuosity, BHA Performance, Data Analytics, Modeling
- 24 in the last 30 days
- 258 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
Given the intensity of drilling operations in the North American unconventional reservoirs and the quality and amount of data gathered during a drilling operation, leveraging those data along with advanced modeling techniques for optimization purposes is becoming more feasible. In this study, historical data and advanced physical modeling are utilized to better understand and optimize the bottom-hole assembly (BHA) performance in drilling operations. A comprehensive data set is gathered for more than 300 BHA runs in the span of three years. This extensive data set enables thorough examination of the variation in the operational parameters and its effect on the drilling performance.
Different indices are used to determine and evaluate drilling performance, such as rate of penetration (ROP). Excessive tortuosity in a well can have many detrimental effects while drilling such as excessive and erratic torque and drag, poor hole cleaning (cuttings removal), low ROP, along with problematic casing and/or liner runs and associated cementing procedures. In this paper, a tortuosity index (TI) is used to quantify the drilled well quality and correlate it to ultimate drilling performance. In the next step, patterns are extracted and used along with physical modeling for optimizing drilling performance before the well is drilled.
The corresponding tortuosity index can be used as a proxy for the well path smoothness and may be used for quantifying parameters affecting drilling performance. According to historical drilling performance data, there appears to be a strong relationship between wellbore tortuosity and ROP. If drilling operating parameters (e.g., BHA configuration, directional company's performance, target formations, bit specification, mud types, etc.) can be related to the TI based on historical data, such parameters can be modified for optimizing the performance before the well is drilled.
By investigating the historical data, different trends have been extracted. In addition, different models can be built to predict drilling performance (e.g., TI) prior to drilling and according to new well design specifications. Based on data from more than 300 BHA runs and using advanced physical modeling, the most strongly correlated parameters to drilling performance have been determined and shown using different case studies. Such a historical database along with modeling techniques are used to predict well quality and drilling performance during the design phase. Using this method, well design specifications can then be optimized to enhance drilling performance and reduce the cost.
|File Size||2 MB||Number of Pages||23|
Ambrus, A., Ashok, P., Chintapalli, A., Ramos, D., Behounek, M., Thetford, T. S., & Nelson, B. (2017, September 5). A Novel Probabilistic Rig Based Drilling Optimization Index to Improve Drilling Performance. Society of Petroleum Engineers. doi:10.2118/186166-MS
Bang, J., Jegbefume, O., Ledroz, A., Weston, J., & Thompson, J. (2017, May 1). Analysis and Quantification of Wellbore Tortuosity. Society of Petroleum Engineers. doi:10.2118/173103-PA
Chen, D. C.-K., Gaynor, T., & Comeaux, B. (2002, January 1). Hole Quality: Why It Matters. Society of Petroleum Engineers. doi:10.2118/74403-MS
Dupriest, F. E., & Koederitz, W. L. (2005, January 1). Maximizing Drill Rates with Real-Time Surveillance of Mechanical Specific Energy. Society of Petroleum Engineers. doi:10.2118/92194-MS
Dupriest, F. E. (2006, January 1). Comprehensive Drill Rate Management Process To Maximize ROP. Society of Petroleum Engineers. doi:10.2118/102210-MS
D'Angelo, J., Ashok, P., van Oort, E., Shahri, M., Nelson, B., Thetford, T., & Behounek, M. (2018, September). Monitoring Wellbore Quality in Real-Time Using a Geometrically Derived Tortuosity Metric. In Unconventional Resources Technology Conference, Houston, Texas, 23-25 July 2018 (pp. 2627–2641). Society of Exploration Geophysicists, American Association of Petroleum Geologists, Society of Petroleum Engineers.
D'Angelo, J., Ashok, P., van Oort, E., Shahri, M., Thetford, T., Nelson, B., … White, M. (2019, March 4). Unplanned Tortuosity Index: Separating Directional Drilling Performance from Planned Well Geometry. Society of Petroleum Engineers. doi:10.2118/194099-MS
Gaynor, T., Hamer, D., Chen, D. C.-K., & Stuart, D. (2002, January 1). Quantifying Tortuosities by Friction Factors in Torque and Drag Model. Society of Petroleum Engineers. doi:10.2118/77617-MS
Gaynor, T. M., Chen, D. C.-K., Stuart, D., & Comeaux, B. (2001, January 1). Tortuosity versus Micro-Tortuosity - Why Little Things Mean a Lot. Society of Petroleum Engineers. doi:10.2118/67818-MS
Menand S., Simon C., Gaombalet J., Macresy L., Gerbaud L., Ben Hamida M., Amghar Y., Denoix H., Cuiller B., Sinardet H.: "PDC Bit Steerability Modeling and Testing for Push-the-bit and Point-the-bit RSS", paper SPE 151283 to be presented at the 2012 IADC/SPE Drilling Conference, 6-8 march, San Diego, CA, USA
Stockhausen, E. J., & Lesso, W. G. (2003, January 1). Continuous Direction and Inclination Measurements Lead to an Improvement in Wellbore Positioning. Society of Petroleum Engineers. doi:10.2118/79917-MS