New Instrument Performance Models for Combined Wellbore Surveys: A Move Toward Optimal Use of Survey Information
- Adrián Ledroz (Gyrodata) | Jon Bang (Gyrodata) | John Weston (Gyrodata)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- December 2016
- Document Type
- Journal Paper
- 307 - 316
- 2016.Society of Petroleum Engineers
- Error Model, Survey Average, Instrument Performance Model, Wellbore position, Positional Uncertainty
- 5 in the last 30 days
- 181 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 10.00|
|SPE Non-Member Price:||USD 30.00|
To confidently determine the path of a wellbore, established practice involves the collection of multiple-survey data by use of the various methods that are available to the industry, such as measurement-while-drilling (MWD) methods using either magnetic or gyroscopic measurements, or surveys taken after a section of the wellbore has been completed, normally using gyroscopic tools. The survey deemed to be of the highest precision, based on published survey-system error models, is commonly selected to be the “definitive survey” for that section of the well and all other data are discarded. However, by combining multiple data sets through the use of survey-averaging techniques, it is possible to obtain a more accurate estimate of wellbore position.
After generating a “combined survey” by such an averaging method (i.e., a survey generated by combining two or more surveys that may be of the same or different type), it is then required to quantify the accuracy of that survey. This may be expressed in the usual manner as a sequence of error ellipsoids at intervals along the path of the well. At present, however, this can only be achieved through rigorous calculations analogous to the survey averaging itself. This is a complex analysis, which is one important reason why survey averaging has not been generally implemented and adopted as a standard analysis practice.
Error models for individual survey tools are usually specified in terms of instrument-performance model (IPM) files in accordance with methods and procedures derived through the work of the SPE Wellbore Positioning Technical Section (SPE-WPTS). The IPM files, along with wellbore-trajectory data, form the inputs to standard error-model software packages, through which survey uncertainty is calculated to a specified level of confidence. This paper demonstrates how new IPM files can be generated for combined surveys. The error analysis resulting from the new IPM file is shown to be consistent with the results obtained through the rigorous mathematical analysis of the individual surveys.
The introduction of new IPM files offers an easy and efficient method for operators to use all available survey information in a consistent manner. This may contribute toward optimization of the surveying program, with implications for both positional uncertainty assessment and safety aspects. Furthermore, the improvement in the positional data as well as the reduced uncertainty that can be achieved by combining surveys may be of significant importance when considering small targets, very long extended-reach wells, and highly congested fields in general, because it might turn unfeasible projects into achievable ones.
|File Size||1 MB||Number of Pages||10|
Alfano, S. and Greer, M. L. 2003. Determining if Two Solid Ellipsoids Intersect. J. Guid. Control Dynam. 26 (1): 106–110. http://dx.doi.org/10.2514/2.5020.
Brooks, A., Wilson, H., Jamieson, A. et al. 2005. Quantification of Depth Accuracy. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 9–12 October. SPE-95611-MS. http://dx.doi.org/10.2118/95611-MS.
Chia, C. R., Phillips, W. J., and Aklestad, D. L. 2003. A New Wellbore Position Calculation Method. SPE Drill & Compl 18 (3): 209–213. SPE-85111-PA. http://dx.doi.org/10.2118/85111-PA.
Ekseth, R., Torkildsen, T., Brooks, A. G. et al. 2010. High-Integrity Wellbore Surveying. SPE Drill & Compl 25 (4): 438–447. SPE-133417-PA. http://dx.doi.org/10.2118/133417-PA.
Grindrod, S. J., Clark, P. J., Lightfoot, J. D. et al. 2016. OWSG Standard Survey Tool Error Model Set for Improved Quality and Implementation in Directional Survey Management. Presented at the IADC/SPE Drilling Conference and Exhibition, Fort Worth, Texas, 1–3 March. SPE-178843-MS. http://dx.doi.org/10.2118/178843-MS.
Landmark. 2015. COMPASS Directional Path Planning, https://www.landmark.solutions/COMPASS-Directional-Well-Path-Planning (accessed 13 November 2015).
Sawaryn, S. J. and Thorogood, J. L. 2005.A Compendium of Directional Calculations Based on the Minimum Curvature Method. SPE Drill & Compl 20 (1): 24–36. SPE-84246-PA. http://dx.doi.org/10.2118/84246-PA.
Thorogood, J. L. 1990. Instrument Performance Models and Their Application to Directional Surveying Operations. SPE Drilling Eng 5 (4): 294–298. SPE-18051-PA. http://dx.doi.org/10.2118/18051-PA.
Thorp, M. 1987. An Analysis of Discrepancies Between Gyro Surveys. Presented at the SPE/IADC Drilling Conference, New Orleans, 15–18 March. SPE-16061-MS. http://dx.doi.org/10.2118/16061-MS.
Torkildsen, T., Håvardstein, S. T., Weston, J. L. et al. 2008. Prediction of Wellbore Position Accuracy When Surveyed With Gyroscopic Tools. SPE Drill & Compl 23 (1): 5–12. SPE-90408-PA. http://dx.doi.org/10.2118/90408-PA.
Williamson, H. S. 2000. Accuracy Prediction for Directional Measurement While Drilling. SPE Drill & Compl 15 (4): 221–233. SPE-67616-PA. http://dx.doi.org/10.2118/67616-PA.