- Boolean operators
- This OR that
This AND that
This NOT that
- Must include "This" and "That"
- This That
- Must not include "That"
- This -That
- "This" is optional
- This +That
- Exact phrase "This That"
- "This That"
- (this AND that) OR (that AND other)
- Specifying fields
- publisher:"Publisher Name"
author:(Smith OR Jones)
Theoretical Basis for Interpretation of Temperature Data During Acidizing Treatment of Horizontal Wells
- Mohammad Tabatabaei (Texas A&M University) | Ding Zhu (Texas A&M University) | Alfred D. Hill (Texas A&M University)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- April 2013
- Document Type
- Journal Paper
- 168 - 180
- 2013. Society of Petroleum Engineers
- 5.1.5 Geologic Modeling, 5.6.11 Reservoir monitoring with permanent sensors, 3.2.4 Acidising, 4.1.2 Separation and Treating
- 0 in the last 30 days
- 536 since 2007
- Show more detail
Optimum fluid placement is crucial for successful acid-stimulation treatments of long horizontal wells where there is a broad variation of reservoir properties along the wellbore. Various methods have been developed and applied in the field to determine the fluid placement and effectiveness of the diversion process, but determining the injection profile during the course of matrix acidizing still remains a challenge. Recently, distributed temperature-sensing (DTS) technology has enabled us to observe the dynamic temperature profile along the wellbore during acid treatments. Quantitative interpretation of dynamic temperature data can provide an invaluable tool to assess the effectiveness of the treatment as well as optimize the treatment through on-the-fly modification of the treatment parameters such as volume, injection rate, and diversion method.
In this paper, we discuss how fluid placement can be quantified using dynamic temperature data. A mathematical model has been developed to simulate the temperature behavior along the wellbore during and shortly after acid treatments. This model couples a wellbore and a near-wellbore flow and thermal model considering the effect of both mass and heat transfer between the wellbore and the formation. The model accounts for all significant thermal processes involved during a treatment, including heat of reaction, conduction, and convection. Then, an inversion procedure is applied to interpret the acid-distribution profile from the measured temperature profiles.
To illustrate how to apply the model and analyze the DTS data, examples of matrix acidizing are presented. The temperature, flow, and pressure data were generated by a horizontal well-acidizing simulator. The inverse model is verified, and the effect of the distribution of stimulation fluid along the lateral and the effectiveness of the diversion processes on the transient temperature response is also discussed. We address some issues regarding solving the inverse problem and discuss the alternative methods of using warm-back information for cases in which inversion is difficult.
Brown, G., Storer, D., McAllister, S. et al. 2003. MonitoringHorizontal Producers and Injectors During Cleanup and Production UsingFiber-Optic-Distributed Temperature Measurements. Presented at the SPE AnnualTechnical Conference and Exhibition, Denver, 5-8 October. SPE-84379-MS. http://dx.doi.org/10.2118/84379-MS.
Clanton, R., Haney, J.A., Pruett, R. et al. 2006. Real-TimeMonitoring of Acid Stimulation Using a Fiber-Optic DTS System. Presented at theSPE Western Regional/AAPG Pacific Section/GSA Cordilleran Section JointMeeting, Anchorage, 8-10 May. SPE-100617-MS. http://dx.doi.org/10.2118/100617-MS.
Glasbergen, G., Gualtieri, D., Trehan, R. et al. 2007.Real-Time Diversion Quantification and Optimization Using DTS. Presented at theSPE Annual Technical Conference and Exhibition, Anaheim, California, USA, 11-14November. SPE-110707-MS. http://dx.doi.org/10.2118/110707-MS.
Glasbergen, G., Gualtieri, D., Van Domelen, M. et al. 2009.Real-Time Fluid Distribution Determination in Matrix Treatments Using DTS.SPE Prod & Oper 24 (1): 135-146. SPE-107775-PA. http://dx.doi.org/10.2118/107775-PA.
Glasbergen, G., Yeager, V.J., Reyes, R.P. et al. 2010.Fluid-Diversion Monitoring: The Key to Treatment Optimization. SPE Prod& Oper 25 (3): 262-274. SPE-122353-PA. http://dx.doi.org/10.2118/122353-PA.
Hastings, W.K. 1970. Monte Carlo sampling methods using Markovchains and their applications. Biometrika 57 (1): 97-109.http://dx.doi.org/10.1093/biomet/57.1.97.
Johnson, D., Sierra, J., and Gualtieri, D. 2006b. SuccessfulFlow Profiling of Gas Wells Using Distributed Temperature Sensing Data.Presented at the SPE Annual Technical Conference, San Antonio, Texas, USA,24-27 September. SPE-103097-MS. http://dx.doi.org/10.2118/103097-MS.
Johnson, D., Sierra, J., Gualtieri, D. et al. 2006a. DTSTransient Analysis: A New Tool To Assess Well-Flow Dynamics. Presented at theSPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 24-27September. SPE-103093-MS. http://dx.doi.org/10.2118/103093-MS.
Kragas, T.K., Williams, B.A., and Myers, G.A. 2001. The OpticOil Field: Deployment and Application of Permanent In-well Fiber Optic SensingSystems for Production and Reservoir Monitoring. Presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans, 30 September-3 October.SPE-71529-MS. http://dx.doi.org/10.2118/71529-MS.
Li, Z. 2010. Predicting Horizontal Well Flow Profiles andWell Optimization by Downhole Temperature and Pressure Data. PhDdissertation, Texas A&M University, College Station, Texas.
Li, Z. and Zhu, D. 2009. Predicting Flow Profile of HorizontalWell by Downhole Pressure and DTS Data for Water-Drive Reservoir. Presented atthe SPE Annual Technical Conference and Exhibition, New Orleans, 4-7 October.SPE-124873-MS. http://dx.doi.org/10.2118/124873-MS.
Marquardt, D. 1963. An Algorithm for Least-Squares Estimationof Nonlinear Parameters. Journal of the Society for Industrial and AppliedMathematics 11 (2): 431-441. http://dx.doi.org/doi:10.1137/0111030.
Mishra, V., Zhu, D., Hill, A.D. et al. 2007. An Acid-PlacementModel for Long Horizontal Wells in Carbonate Reservoirs. Presented at theEuropean Formation Damage Conference, Scheveningen, The Netherlands, 30 May-1June. SPE-107780-MS. http://dx.doi.org/10.2118/107780-MS.
Oliver, D., Cunha, L., and Reynolds, A. 1997. Markovchain Monte Carlo methods for conditioning a permeability field to pressuredata. Math. Geol. 29 (1): 61-91. http://dx.doi.org/10.1007/bf02769620.
Oliver, D.S., Reynolds, A.C., and Liu, N. 2008. InverseTheory for Petroleum Reservoir Characterization and History Matching.Cambridge, UK: Cambridge University Press.
Ramey, H.J. Jr. 1962. Wellbore Heat Transmission. J PetTechnol 14 (4): 427-435. SPE-96-PA. http://dx.doi.org/10.2118/96-PA.
Robert, C. and Casella, G. 1999. Monte Carlo StatisticalMethods. New York: Springer-Verlag.
Sui, W., Zhu, D., Hill, A.D. et al. 2008b. Model for TransientTemperature and Pressure Behavior in Commingled Vertical Wells. Presented atthe SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, 28-30October. SPE-115200-MS. http://dx.doi.org/10.2118/115200-MS.
Sui, W., Zhu, D., Hill, A.D. et al. 2008a. DeterminingMultilayer Formation Properties From Transient Temperature and PressureMeasurements. Presented at the SPE Annual Technical Conference and Exhibition,Denver, 21-24 September. SPE-116270-MS. http://dx.doi.org/10.2118/116270-MS.
Tabatabaei, M. 2011. Real-Time Evaluation of Stimulation andDiversion in Horizontal Wells. PhD dissertation, Texas A&M University,College Station, Texas.
Tabatabaei, M., Tan, X., Hill, A.D. et al. 2011a. WellPerformance Diagnosis with Temperature Profile Measurements. Presented at theSPE Annual Technical Conference and Exhibition, Denver, 30 October-2 November.SPE-147448-MS. http://dx.doi.org/10.2118/147448-MS.
Tabatabaei, M., Zhu, D., and HIll, D. 2011b. Interpretation ofTemperature Data during Acidizing Treatment of Horizontal Wells for StimulationOptimization. Presented at the International Petroleum Technology Conference,Bangkok, Thailand, 7-9 February. IPTC-15214-MS. http://dx.doi.org/10.2523/15214-MS.
Tan, X., Tabatabaei, M., Zhu, D. et al. 2011. Measurement ofAcid Placement with Temperature Profiles. Presented at the SPE EuropeanFormation Damage Conference, Noordwijk, The Netherlands, 7-10 June.SPE-144194-MS. http://dx.doi.org/10.2118/144194-MS.
Tan, X., Zhu, D., and Hill, A.D. 2009. Determining AcidDistribution Using Distributed Temperature Measurements. Presented at the SPEAnnual Technical Conference and Exhibition, New Orleans, 4-7 October.SPE-124743-MS. http://dx.doi.org/10.2118/124743-MS.
Tardy, P.M.J. and Chang, F.F. 2011. Determining MatrixTreatment Performance From Downhole Pressure And Temperature Distribution: AModel. Presented at the 2011 International Petroleum Technology Conference,Bangkok, Thailand, 15-17 November. IPTC-15118-MS.
Tardy, P.M.J., Ramondenc, P., Weng, X. et al. 2012. Inversionof Distributed-Temperature-Sensing Logs To Measure Zonal Coverage During andAfter Wellbore Treatments With Coiled Tubing. SPE Prod & Oper 27 (1): 78-86. SPE-143331-PA. http://dx.doi.org/10.2118/143331-PA.
Wadsley, A.W. 2005. Markov Chain Monte Carlo Methods forReserves Estimation. Presented at the International Petroleum TechnologyConference, Doha, Qatar, 21-23 November. IPTC-10065-MS. http://dx.doi.org/10.2523/10065-MS.
Wang, X., Lee, J., Thigpen, B. et al. 2008. Modeling FlowProfile Using Distributed Temperature Sensor (DTS) System. Presented at theIntelligent Energy Conference and Exhibition, Amsterdam, 25-27 January. SPE-111790-MS. http://dx.doi.org/10.2118/111790-MS.
Yoshioka, K., Zhu, D., Hill, A.D. et al. 2007. Prediction ofTemperature Changes Caused by Water or Gas Entry Into a Horizontal Well. SPEProd & Oper 22 (4): 425-433. SPE-100209-PA. http://dx.doi.org/10.2118/100209-PA.
Yoshioka, K., Zhu, D., Hill, A.D. et al. 2009. A New InversionMethod to Interpret Flow Profiles From Distributed Temperature and PressureMeasurements in Horizontal Wells. SPE Prod & Oper 24(4): 510-521. SPE-109749-PA. http://dx.doi.org/10.2118/109749-PA.
Not finding what you're looking for? Some of the OnePetro partner societies have developed subject- specific wikis that may help.
The SEG Wiki
The SEG Wiki is a useful collection of information for working geophysicists, educators, and students in the field of geophysics. The initial content has been derived from : Robert E. Sheriff's Encyclopedic Dictionary of Applied Geophysics, fourth edition.