Principal Component Analysis for the Study of Opening Underground Caverns in Salt Rocks
Keywords:cavern, salt rock, process variables, numerical simulations, statistical analysis
The constant dynamism within the oil industry associated with the need for new technologies in terms of production and disposal of products were fundamental for the increase of studies about the use of underground caverns in salt rocks as an alternative for the storage of petroleum products. Salt rock is particularly useful for storage because of its low cost, low permeability, and its healing potential when compared to other rocks, including granite, mud, and basalt. The opening process and subsequent development of these cavities are complex activities and the variables involved in the process play a crucial role during the entire operation. In this sense, the present work aims to identify, through the PCA (Principal Component Analysis) statistical tool, the variables that most influence the process of opening a salt cavern by dissolution. For this, numerical simulations of the dissolution mining process for opening a cavern under typical conditions of water injection into a salt rock using the software SALGAS were developed considering different methods of saline water circulation, after that, the variables injection temperature, injection rate, radius, volume, pump power, cumulative energy, tubing loss, produced brine, pump pressure, injection pressure, and salt dissolution factor were interpreted using the multivariate statistical tool through software PAST. For the simulations generated, the results with the statistical tool were satisfactory, it was found that the brine injection rate contributes significantly to the process, in terms of x-axis, directly influencing the behavior of other variables, the temperature have a great importance to the y-axis. Regarding the total variability of the data, more than 97% of these could be represented in terms of the first two components for both scenarios studied.
H. Mirzabozorg, K. Nazokkar, R. J. Chalaturny, and S. Nazary Moghadam. “Parametric assessment of salt cavern performance using a creep model describing dilatancy and failure”. International Journal of Rock Mechanics and Mining Sciences, vol. 79, pp. 250-267, 2015.
S. Nazary Moghadam, H. Mirzabozorg, and A. Noorzad. “Modeling time dependent behavior of gas caverns in rock salt considering creep, dilatancy and failure”. Tunneling and Underground Space Technology, vol. 33, pp. 171-185, 2013.
X. Yang and X. Liu. “Numerical simulation of rock salt dissolution in dynamic water”. Environmental Earth Sciences, vol. 76, pp. 1-10, 2017.
R. W. Durie and F. W. Jessen, “Mechanism of the Dissolution of Salt in the Formation of Underground Salt Cavities”. Society of Petroleum Engineers Journal, vol. 4, n. 2, pp. 183-190, 1964.
A. Saberian. Numerical Simulation of Development of Solution-Mined Salt Cavities. 1974.
X. Yang, X. Liu, W. Zang, Z. Lin and Q. Wang. “A Study of Analytical Solution for the Special Dissolution Rate Model of Rock Salt”. Advances in Materials Science and Engineering, vol. 2017, pp. 1-8, 2017.
D. F. FERREIRA. Estatística Multivariada. 2.ed. Lavras: UFLA, 2011, vol.1, pp. 1-676.
J. Alonso-Gutierrez et al., “Principal Component Analysis of Proteomics (PCAP) as A Tool to Direct Metabolic Engineering”. Metabolic Engineering, vol. 28, pp. 123 – 133, 2015.
J. K. Warren. Evaporites: Sediments, Resources and Hydrocarbons. Berlin: Springer, 2006, pp. 1-1036.
T. Eyerman, SALGAS and SalGas for Windows User’s Manual. pp. 1-53, 2008.
A. Saberian. SALGAS User’s Manual, Volume 1 and 2. Solution Mining Research Institute, Clarks Summnit, PA, 1984.
K. Hongyu, V. L. M. Sandanielo and G. J. Junior. “Principal Component Analysis: theory, interpretations and applications”. E&S - Engineering and Science, vol.1, n. 5, pp. 83-90, 2015.
R. A. Johnson, D. W. Wichern. Applied multivariate statistical analysis. Madison: Prentice Hall International, pp. 1-816, 1998.
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