3D visualization of hydraulic fractures using micro-seismic monitoring: Methodology and application

Chenghua Ou , Chenggang Liang , Zhaoliang Li , Li Luo , Xiao Yang

Petroleum ›› 2022, Vol. 8 ›› Issue (1) : 92 -101.

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Petroleum ›› 2022, Vol. 8 ›› Issue (1) :92 -101. DOI: 10.1016/j.petlm.2021.03.003
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3D visualization of hydraulic fractures using micro-seismic monitoring: Methodology and application
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Abstract

In this paper, a new 3D visualization technical method was developed for hydraulic fractures using micro-seismic monitoring. This technical method consists of four steps: i. interpret the geologic hydraulic fracture model based on seismic source location data from micro-seismic monitoring; ii. develop a hydraulic fracture indication model, relying on the 3D spatial freeze-frame of micro-seismic monitoring sources from hydraulic fracturing; iii. construct a hydraulic fracture density model using the intensity from the micro-seismic monitoring; and iv. implement a 3D visualization of the hydraulic fractures, relying on the spatial constraints of the density model, the hydraulic fracture indication model, and the properties of the hydraulic fractures. This proposed technical method was used to produce 3D visualizations of the hydraulic fractures in well X in the Jiao reservoir, China, and the 3D visualizations of the distribution, development, extent and cutting relationships of hydraulic fractures were successfully realized. The results show that this technical method can be used as a practical and reliable approach to characterize hydraulic fractures.

Keywords

3D visualization / Micro-seismic monitoring / Hydraulic fracture / Jiao reservoir / Reservoir modelling

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Chenghua Ou, Chenggang Liang, Zhaoliang Li, Li Luo, Xiao Yang. 3D visualization of hydraulic fractures using micro-seismic monitoring: Methodology and application. Petroleum, 2022, 8(1): 92-101 DOI:10.1016/j.petlm.2021.03.003

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Acknowledgements

We are grateful for the support of the National Major Basic Research Development Program of China (2014CB239205), the Sichuan Science and Technology Program (Grant No. 2021YFQ0049)and the sub-project of the National Science and Technology Major Project (Grant No. 2017ZX05035003).

References

[1]

R. Aguilera, Flow units: from conventional to tight-gas to shale-gas to tight-oil to shale-oil reservoirs, SPE Reservoir Eval. Eng. 17 (2014) 190-208, https://doi.org/10.2118/165360-PA.

[2]

Z. Caineng, Y. Zhi, Z. Rukai, Z. Guosheng, H. Lianhua, W. Songtao, W. Lan, Progress in China’s unconventional oil & gas exploration and development and theoretical technologies, Acta Geol. Sin. 89 (2015) 938-971, https://doi.org/10.1111/1755-6724.12491.

[3]

C.H. Ou, R. Ray, C.C. Li, H. Yong, Multi-index and two-level evaluation of shale gas reserve quality, J. Nat. Gas Sci. Eng. 35 (2016) 1139-1145, https://doi.org/10.1016/j.jngse.2016.09.056.

[4]

C.H. Ou, C.C. Li, D.M. Zhi, L. Xue, S.G. Yang, Coupling accumulation model with gas-bearing features to evaluate low-rank coalbed methane resource potential in the southern Junggar Basin, China, AAPG (Am. Assoc. Pet. Geol.) Bull. 102 (2018) 153-174, https://doi.org/10.1306/03231715171.

[5]

R. Wu, O. Kresse, X. Weng, C.E. Cohen, H. Gu, Modeling of interaction of hydraulic fractures in complex fracture networks, in: SPE Hydraulic Fracturing Technology Conference, the Woodlands, Texas, USA, February 2012 (6-8). SPE-152052, 2012.

[6]

C.H. Yew, X. Weng, Mechanics of Hydraulic Fracturing, Gulf Professional Publishing, 2014, pp. 23-49.

[7]

C.H. Ou, C.C. Li, S.Y. Huang, W.T. Lu, J.S. James, H.L. Xiong, Three-dimensional discrete network modeling of structural fractures based on the geometric restoration of structure surface: methodology and its application, J. Petrol. Sci. Eng. 161 (2018b) 417-426, https://doi.org/10.1016/j.petrol.2017.12.007.

[8]

C.H. Ou, C.C. Li,3D Discrete Network Modeling of Shale Bedding Fractures Based on Lithofaices, vol. 44, Petroleum Exploration and Development, 2017, pp. 1-10, https://doi.org/10.11698/PED.2017.02.18.

[9]

J. Dahl, K. Dhuldhoya, R. Vaidya, J. Tucker, J. Samaripa, B. Johnson, R. Dusterhoft, An evaluation of completion effectiveness in hydraulically fractured wells and the assessment of refracturing scenarios, in: SPE Hydraulic Fracturing Technology Conference, the Woodlands, Texas, USA, February 2016 (9-11). SPE-179136, 2016.

[10]

J.C. Li, B. Gong, H.G. Wang, Mixed integer simulation optimization for optimal hydraulic fracturing and production of shale gas fields, Eng. Optim. 48 (2016) 1378-1400, https://doi.org/10.1080/0305215X.2015.1111002.

[11]

W. Zhou, R. Banerjee, B.D. Poe, J. Spath, M. Thambynayagam, Semi analytical production simulation of complex hydraulic-fracture networks, SPE J. 19 (2014) 6-18.

[12]

G.E. King, Overview of hydraulic fracturing operations and technologies, in: V. Uddamer, A. Morse, K.J. Tindle (Hydraulic Fracturing Impacts and Technologies:Eds.), A Multidisciplinary Perspective, CRC Press, 2015, pp. 1-20, https://doi.org/10.1016/j.jngse.2015.12.020.

[13]

N.R. Warpinski, Understanding hydraulic fracture growth, effectiveness, and safety through microseismic monitoring, in: ISRM International Conference for Effective and Sustainable Hydraulic Fracturing, International Society for Rock Mechanics, Brisbane, Australia, May 2013 (20-22), 2013. ISRM-ICHF-2013-047.

[14]

E. Murminacho, H. Sanchez, M. Lopez, R.G. Rachid, J. Maniere, A. Milne, Increasing production and reserves in a mature field with hydraulic fracturing by combining fracture pressure analysis, pressure transient analysis, and rate transient analysis, in: SPE Latin American and Caribbean Petroleum Engineering Conference, Quito, Ecuador, November 2015, 2015, pp. 18-20. SPE-177027.

[15]

S. Al-Rbeawi, How much stimulated reservoir volume and induced matrix permeability could enhance unconventional reservoir performance, J. Nat. Gas Sci. Eng. 46 (2017) 764-781, https://doi.org/10.1016/j.jngse.2017.08.017.

[16]

H.R. Hardy Jr.,Acoustic Emission/micro Seismic Activity: Volume 1: Principles, Techniques and Geotechnical Applications, vol. 1, A. A. Balkema Publishers, USA, 2005, pp. 28-103.

[17]

M. Salah, A. Bereak, M.A. Gabry, T. Batmaz, M. El-Sebaee, A. Abdel-Halim, Microseismic monitoring improves hydraulic fracturing diagnostic and optimizes field development in Western Desert, Egypt, in: Offshore Technology Conference, Houston, Texas, USA, May 2016 (2-5), 2016. OTC-26864.

[18]

M. Van Der Baan, D. Eaton, M. Dusseault, Microseismic monitoring developments in hydraulic fracture stimulation, in: ISRM International Conference for Effective and Sustainable Hydraulic Fracturing, Brisbane, Australia, May 2013 (20-22), 2013. ISRM-ICHF-2013-003.

[19]

T. Fischer, S. Hainzl, L. Eisner, S.A. Shapiro, J. Le Calvez, Micro seismic signatures of hydraulic fracture growth in sediment formations: observations and modelling, J. Geophys. Res.: Solid Earth 113 (2008) B02307.

[20]

J. Le Calvez, J. Zhang, O. Harrasi, Y. El-Taha, M. Eltilib, M. El Gihani, T. Al- Wadhahi,Multi-well hydraulic fracture monitoring in the sultanate of Oman using surface and downhole micro seismic arrays, 6th EAGE Workshop on Passive Seismic 31 (January 2016).

[21]

O. Peyret, J. Drew, M. Mack, K. Brook, S.C. Maxwell, C.L. Cipolla, Subsurface to surface microseismic monitoring for hydraulic fracturing, in: SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, October 2012 (8-10), 2012. SP--159670.

[22]

K. Kim, Discrete modeling of hydraulic fracturing processes in a complex preexisting fracture network, MR41A-2626, in: AGU Fall Meeting, Thursday, 17 December 2015, San Francisco, USA, 2015.

[23]

A. Yaghoubi, M. Zoback, Hydraulic Fracturing Modeling Using a Discrete Fracture Network in the Barnett Shale, Stanford Stress and Geomechanics Group, American Geophysical Union Fall Meeting, 2016, https://doi.org/10.1016/j.ijrmms.2019.01.015. F6-1 to F6-21.

[24]

S.V. Yaskevich, V.Y. Grechka, A.A. Duchkov, Processing microseismic monitoring data, considering seismic anisotropy of rocks, J. Min. Sci. 51 (2015) 477-486, https://doi.org/10.1134/S1062739115030084.

[25]

F.D. Shmakov, Surface microseismic monitoring of hydraulic fracture: data processing and interpretation, Seismic Technology 9 (2012) 1-10, https://doi.org/10.3997/2405-7495.2015022.

[26]

Y. Tan, C. He, X. Hou, J. Yu, G. Feng, Detection and location of microseismic events with low signal-to-noise ratios, in: International Petroleum Technology Conference, Kuala Lumpur, Malaysia, December, 2014 (10-12), 2014. IPTC-17930.

[27]

S. Maxwell, Microseismic location uncertainty, CSEG Recorder 34 (2009) 41-46.

[28]

F. Stanék, L. Eisner, T. Jan Moser, Stability of source mechanisms inverted from P-wave amplitude microseismic monitoring data acquired at the surface, Geophys. Prospect. 62 (2014) 475-490, https://doi.org/10.1111/1365-2478.12107.

[29]

C.H. Ou, W. Chen, Z. Ma, Quantitative identification and analysis of subseismic extensional structure system: technique schemes and processes, J. Geophys. Eng. 12 (2015) 502-514, https://doi.org/10.1088/1742-2132/12/3/502.

[30]

C.H. Ou, W. Chen, C.C. Li, Using structure restoration maps to comprehensively identify potential faults and fractures in compressional structures, J. Cent. S. Univ. 23 (2016) 677-684.

[31]

C.H. Ou, C.C. Li, S.Y. Huang, J.S. James, Y. Xu, Fine reservoir structure modeling based upon 3D visualized stratigraphic correlation between horizontal wells: methodology and its application, J. Geophys. Eng. 14 (2017) 1557-1571, https://doi.org/10.1088/1742-2140/aa871e.

[32]

C.H. Ou, C.C. Li, S.Y. Huang, J.S. James, Remigration and leakage from continuous shale reservoirs: insights from the Sichuan Basin and its periphery, China, AAPG (Am. Assoc. Pet. Geol.) Bull. 103 (2019) 2009-2030, https://doi.org/10.1306/12191817069.

[33]

C.H. Ou, X.L. Wang, C.C. Li, Y. He, Three-dimensional modelling of a multilayer sandstone reservoir: the Sebei Gas Field, China, Acta Geologica Sinica-English Edition 90 (2016) 801-840.

[34]

C.H. Ou, C.C. Li, Z. Ma, 3D Modeling of gas/water distribution in water-bearing carbonate gas reservoirs: the Longwangmiao Gas Field, China, J. Geophys. Eng. 13 (2016) 745-757, https://doi.org/10.1088/1742-2132/13/5/745.

[35]

B.D. Ripley,Stochastic Simulation, vol. 316, John Wiley Sons, USA, 2009, pp. 96-118.

[36]

R. Dimitrakopoulos, X. Luo, Generalized sequential Gaussian simulation on group size n and screen-effect approximations for large field simulations, Math. Geol. 36 (2004) 567-591.

[37]

C.C. Li, C.H. Ou, Modes of shale-gas enrichment controlled by tectonic evolution, Acta Geol. Sin. 92 (2018) 1934-1947, https://doi.org/10.1111/1755-6724.13686. English Edition.

[38]

C.H. Ou, C.C. Li, Z.H. Rui, Q. Ma, Lithofacies distribution and gas-controlling characteristics of the WufengeLongmaxi black shales in the southeastern region of the Sichuan Basin, China, J. Petrol. Sci. Eng. 165 (2018) 269-283, https://doi.org/10.1016/j.petrol.2018.02.024.

[39]

C.H. Ou, W. Chen, C.C. Li, W.J. Zhou, Structural geometrical analysis and simulation of decollement growth folds in piedmont Fauqi Anticline of Zagros Mountains, Iraq, Sci. China Earth Sci. 59 (2016) 1885-1898, https://doi.org/10.1007/s11430-016-5332-6.

[40]

T.L. Guo, H. Zhang, Formation and enrichment mode of jiaoshiba shale gas field, Sichuan Basin, Pet. Explor. Dev. 41 (2014) 31-40. https://doi.org/10.1016/S1876-3804(14)60003-3.

[41]

X. Guo, D. Hu, Y. Li, R. Liu, Q. Wang, Geological features and reservoiring mode of shale gas reservoirs in Longmaxi Formation of the Jiaoshiba Area, Acta Geol. Sin. 88 (2014) 1811-1821, https://doi.org/10.1111/1755-6724.1234710.1016/S1876-3804(14)60003-3.

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