New Insights into Carbonate Matrix Acidizing Treatments: A Mathematical and Experimental Study
- Mahmoud T. Ali (Texas A&M University) | Hisham A. Nasr-El-Din (Texas A&M University)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2020
- Document Type
- Journal Paper
- 1,272 - 1,284
- 2020.Society of Petroleum Engineers
- acidizing, carbonate reservoirs, simulation
- 31 in the last 30 days
- 109 since 2007
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The design process of carbonate matrix acidizing treatments requires coring and conducting linear, radial coreflood experiments. With the current environment revolving around cutting costs, it has become increasingly important to accurately design cost-effective acidizing treatments. This work aims to introduce a novel approach to predicting the performance of acid treatments in the field using log data only. A radial reactive flow simulator, using porosity distributed from logs, is used to provide accurate predictions without the need for experiments.
Coreflood acidizing experiments at 150 and 200°F with two acid concentrations were studied. A reactive flow simulator was built using porosity distribution derived from computed-tomography (CT) scans and tuned to match experimental data. A new radial simulation model of 3.25-ft radius was used to study acid propagation under field conditions. For accurate predictions, porosity was distributed using values derived from cores’ CT scans. Simulation results were compared with traditional 1D models. Different porosity distributions, including gamma distributions, were used in the radial model.
The reactive flow simulator was able to accurately capture wormhole propagation inside the linear core. A greater than 90% match between the experimental and the simulated acid pore volume (PV) to breakthrough (PVBT) was obtained using two acid concentrations’ different temperatures. The simulation results from the radial field-scale model show that the optimal velocity can be higher or lower than those predicted from laboratory experiments. Accordingly, caution must be taken when linear coreflood data are used to predict acid propagation in the field. The simulations showed that traditional upscaling models overpredict acid volumes; the predicted volumes are double at moderate to high injection rates. Models using statistically distributed porosity can provide accurate acidpropagation predictions, with a relative percentage error of less than 25% at extremely high injection rates.
This work introduces an accurate model using porosity directly from logs to predict acid performance while avoiding expensive designs. The simulation results reveal that traditional designs overpredict acid volumes required for field treatments. The statistically distributed porosity can be used as a substitute for CT-scan-derived porosity with a low effect on model predictability. The reactive flow simulator can accurately match experimental data.
|File Size||2 MB||Number of Pages||13|
Ali, M. T. and Nasr-El-Din, H. A. 2019. A Robust Model to Simulate Dolomite-Matrix Acidizing. SPE Prod & Oper 34 (1): 109–129. SPE-191136-PA. https://doi.org/10.2118/191136-PA.
Ali, M. T. and Ziauddin, M. E. 2020. Carbonate Acidizing: A Mechanistic Model for Wormhole Growth in Linear and Radial Flow. J Pet Sci Eng 186: 106776. https://doi.org/10.1016/j.petrol.2019.106776.
Ali, M. T., Ezzat, A. A., and Nasr-El-Din, H. A. 2020. A Model to Simulate Matrix Acid Stimulation for Wells in Carbonate Reservoirs with Vugs and Natural Fractures. SPE J. SPE-199341-PA 25 (2): 609–631. SPE-199341-PA. https://doi.org/10.2118/199341-PA.
Balakotaiah, V. and West, D. H. 2002. Shape Normalization and Analysis of the Mass Transfer Controlled Regime in Catalytic Monoliths. Chemical Engineering Science 57 (8): 1269–1286. https://doi.org/10.1016/S0009-2509(02)00059-3.
Bazin, B. 2001. From Matrix Acidizing to Acid Fracturing: A Laboratory Evaluation of Acid/Rock Interactions. SPE Prod & Fac 16 (1): 22–29. SPE-66566-PA. https://doi.org/10.2118/66566-PA.
Beletskaya, A., Ivanov, E., Stukan, M. et al. 2017. Reactive Flow Modeling at Pore Scale. Paper presented at the SPE Russian Petroleum Technology Conference, Moscow, Russia, 16–18 October. SPE-187805-MS. https://doi.org/10.2118/187805-MS.
Buijse, M. A. and Glasbergen, G. 2005. A Semi-Empirical Model to Calculate Wormhole Growth in Carbonate Acidizing. Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, USA, 9–12 October. SPE-96892-MS. https://doi.org/10.2118/96892-MS.
Carman, C. 1956. Flow of Gases through Porous Media, first edition. New York, New York, USA: Academic Press.
Daccord, G., Lenormand, R., and Liétard, O. 1993. Chemical Dissolution of a Porous Medium by a Reactive Fluid—I. Model for the “Wormholing” Phenomenon. Chem Eng Sci 48 (1): 169–178. https://doi.org/10.1016/0009-2509(93)80293-Y.
Dong, K., Jin, X., Zhu, D. et al. 2014. The Effect of Core Dimensions on the Optimal Acid Flux in Carbonate Acidizing. Paper presented at the SPE International Symposium and Exhibition on Formation Damage Control, Lafayette, Louisiana, USA, 26–28 February. SPE-168146-MS. https://doi.org/10.2118/168146-MS.
Dong, K., Zhu, D., and Hill, A. D. 2016. Theoretical and Experimental Study on Optimal Injection Rates in Carbonate Acidizing. Paper presented at the SPE International Conference and Exhibition on Formation Damage Control, Lafayette, Louisiana, USA, 24–26 February. SPE-178961-MS. https://doi.org/10.2118/178961-MS.
Fredd, C. N. and Fogler, H. S. 1998. Influence of Transport and Reaction on Wormhole Formation in Porous Media. AIChE J. 44 (9): 1933. https://doi.org/10.1002/aic.690440902.
Fredd, C. N. and Fogler, H. S. 1999. Optimum Conditions for Wormhole Formation in Carbonate Porous Media: Influence of Transport and Reaction. SPE J. 4 (3): 196–205. SPE-56995-PA. https://doi.org/10.2118/56995-PA.
Furui, K., Burton, R., Burkhead, D. et al. 2012. A Comprehensive Model of High-Rate Matrix-Acid Stimulation for Long Horizontal Wells in Carbonate Reservoirs: Part I—Scaling Up Core-Level Acid Wormholing to Field Treatments. SPE J. 17 (1): 271–279. SPE-134265-PA. https://doi.org/10.2118/134265-PA.
Ghommem, M., Zhao, W., Dyer, S. et al. 2015. Carbonate Acidizing: Modeling, Analysis, and Characterization of Wormhole Formation and Propagation. J Pet Sci Eng 131 (July): 18–33. https://doi.org/10.1016/j.petrol.2015.04.021.
Gupta, N. and Balakotaiah, V. 2001. Heat and Mass Transfer Coefficients in Catalytic Monoliths. Chemical Engineering Science 56 (16): 4771–4786. https://doi.org/10.1016/S0009-2509(01)00134-8.
Lund, K., Fogler, H. S., and McCune, C. C. 1973. Acidization—I. The Dissolution of Dolomite in Hydrochloric Acid. Chem Eng Sci 28 (3): 691–700. https://doi.org/10.1016/0009-2509(77)80003-1.
Lund, K., Fogler, H. S., McCune, C. C. et al. 1975. Acidization—II. The Dissolution of Calcite in Hydrochloric Acid. Chem Eng Sci 30 (8): 825–835. https://doi.org/10.1016/0009-2509(75)80047-9.
Maheshwari, P. and Balakotaiah, V. 2013. Comparison of Carbonate HCl Acidizing Experiments with 3D Simulations. SPE Prod & Oper 28 (4): 402–413. SPE-164517-PA. https://doi.org/10.2118/164517-PA.
McDuff, D., Jackson, S., Shuchart, C. et al. 2010. Understanding Wormholes in Carbonates: Unprecedented Experimental Scale and 3D Visualization. J Pet Technol 62 (10): 78–81. SPE-129329-JPT. https://doi.org/10.2118/129329-JPT.
Nishikata, E., Ishii, T., and Ohta, T. 1981. Viscosities of Aqueous Hydrochloric Acid Solutions, and Densities and Viscosities of Aqueous Hydroiodic Acid Solutions. J. Chem. Eng. Data 26 (3): 254–256. https://doi.org/10.1021/je00025a008.
Panga, M. K. R., Balakotaiah, V., and Ziauddin, M. 2002. Modeling, Simulation and Comparison of Models for Wormhole Formation During Matrix Stimulation of Carbonates. Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 29 September–2 October. SPE-77369-MS. https://doi.org/10.2118/77369-MS.
Panga, M. K. R., Ziauddin, M., and Balakotaiah, V. 2005. Two-Scale Continuum Model for Simulation of Wormholes in Carbonate Acidization. AIChE J. 51 (12): 3231–3248. https://doi.org/10.1002/aic.10574.
Schneider, C. A., Rasband, W. S., and Eliceiri, K. W. 2012. NIH Image to ImageJ: 25 Years of Image Analysis. Nature Methods 9: 671–675.
Schwalbert, M. P., Hill, A. D., and Zhu, D. 2019. A New Up-Scaled Wormhole Model Grounded on Experimental Results and in 2-Scale Continuum Simulations. Paper presented at the SPE International Conference on Oilfield Chemistry, Galveston, Texas, USA, 8–9 April. SPE-193616-MS. https://doi.org/10.2118/193616-MS.
Tardy, P. M. J., Lecerf, B., and Christanti, Y. 2007. An Experimentally Validated Wormhole Model for Self-Diverting and Conventional Acids in Carbonate Rocks Under Radial Flow Conditions. Paper presented at the European Formation Damage Conference, Scheveningen, The Netherlands, 30 May–1 June. SPE-107854-MS. https://doi.org/10.2118/107854-MS.
Taylor, K. C., Nasr-El-Din, H. A., and Mehta, S. 2006. Anomalous Acid Reaction Rates in Carbonate Reservoir Rocks. SPE J. 11 (4): 488–496. SPE-89417-PA. https://doi.org/10.2118/89417-PA.
Wang, Y., Hill, A. D., and Schechter, R. S. 1993. The Optimum Injection Rate for Matrix Acidizing of Carbonate Formations. Paper presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 3–6 October. SPE-26578-MS. https://doi.org/10.2118/26578-MS.
Zakaria, A. S., Nasr-El-Din, H. A., and Ziauddin, M. 2015. Predicting the Performance of the Acid-Stimulation Treatments in Carbonate Reservoirs with Nondestructive Tracer Tests. SPE J. 20 (6): 1238–1253. SPE-174084-PA. https://doi.org/10.2118/174084-PA.
Ziauddin, M. E. and Bize, E. 2007. The Effect of Pore Scale Heterogeneities on Carbonate Stimulation Treatments. Paper presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 11–14 March. SPE-104627-MS. https://doi.org/10.2118/104627-MS.