Research status and prospect of intelligent wells reservoir monitoring technology
Source abstract
Abstract
Intelligent wells technology is an emerging reservoir production management technology, and its monitoring technology can obtain reservoir parameters, monitor reservoir conditions, formulate reservoir exploitation plans, and predict production dynamics, which plays a vital role in reservoir production management. Intelligent wells monitoring technology is mainly divided into two categories: near-well monitoring and deep monitoring. Near-well monitoring covers the development of downhole pressure, temperature, flow rate, and other measurement technologies, as well as related sensors and devices. Deep monitoring includes the latest technologies such as flow potential, inter-well electromagnetic imaging, seismic monitoring, four-dimensional gravity, radar imaging, distributed fibre optic sensing technology, and artificial intelligence-oriented monitoring technology. We investigate domestic and international reservoir monitoring technologies, compare their characteristics, analyse the advantages and disadvantages, summarise the current status and trends, and put forward suggestions for further development.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Reservoir Engineering and Simulation Methods · Drilling and Well Engineering · Hydraulic Fracturing and Reservoir Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Southwest Petroleum University
Newcastle University
Funding
National Natural Science Foundation of China · Nanchong-Southwest Petroleum University City-School Science and Technology Strategic Cooperation Program · Natural Science Starting Project of SWPU · Sichuan Science and Technology Program
References (100+)
Show source-provided references
1. 10.1016/j.fuel.2017.08.09510.1016/j.fuel.2017.08.095 ↗
2. 10.1109/JSYST.2016.260638110.1109/JSYST.2016.2606381 ↗
3. 10.3969/j.issn.1004-5716.2014.04.01310.3969/j.issn.1004-5716.2014.04.013 ↗
4. 10.1080/10589759.2019.159735610.1080/10589759.2019.1597356 ↗
5. 10.1080/10589759.2024.230646910.1080/10589759.2024.2306469 ↗
6. 10.1080/10589759.2022.214222310.1080/10589759.2022.2142223 ↗
7. 10.1080/10589759.2023.229708110.1080/10589759.2023.2297081 ↗
8. 10.1080/10589759.2024.232762210.1080/10589759.2024.2327622 ↗
9. 10.1080/1058975060078490210.1080/10589750600784902 ↗
10. Yao J, Liu J, Zhang K. Intelligent wells technology abroad. Beijing: Petroleum Industry Press; 2011.
11. 10.1016/j.fuel.2023.12882610.1016/j.fuel.2023.128826 ↗
12. 10.13301/j.cnki.ct.2024.02.04810.13301/j.cnki.ct.2024.02.048 ↗
13. 10.1016/j.jngse.2015.09.02010.1016/j.jngse.2015.09.020 ↗
14. 10.3969/j.issn.1006-6535.2014.04.0010.3969/j.issn.1006-6535.2014.04.00 ↗
15. 10.1021/acs.energyfuels.3c0309810.1021/acs.energyfuels.3c03098 ↗
16. 10.6038/pg2013061310.6038/pg20130613 ↗
17. 10.1190/1.305922410.1190/1.3059224 ↗
18. 10.16489/j.issn.1004-1338.2015.04.00510.16489/j.issn.1004-1338.2015.04.005 ↗
19. 10.2118/193808-PA10.2118/193808-PA ↗
20. Li G, Zhu F, Ren L, et al. Application of microseismic water injection front monitoring technology in the middle and deep oil reservoirs of Gaoshangbao. Spec Oil Gas Reservoirs. 2010;17(4):104–106+126.
21. 10.13810/j.cnki.issn.1000-7210.2021.02.01610.13810/j.cnki.issn.1000-7210.2021.02.016 ↗
22. Zhou F. Research progress in intelligent wells monitoring technology. Geological Sci Technol Inf. 2013;32(2):174–180.
23. 10.2118/209257-PA10.2118/209257-PA ↗
24. 10.1109/JSTARS.2024.340602210.1109/JSTARS.2024.3406022 ↗
25. 10.1016/j.jhydrol.2024.13169110.1016/j.jhydrol.2024.131691 ↗
26. 10.2118/208682-PA10.2118/208682-PA ↗
27. 10.2118/0321-0051-JPT10.2118/0321-0051-JPT ↗
28. 10.2118/199890-PA10.2118/199890-PA ↗
29. Kong B, Liu A, Xu X, et al. Integrated monitoring technology of capillary downhole temperature and pressure based on fiber optic temperature measurement. Instrument Technol Sensors. 2019;7:101–105.
30. 10.3969/j.issn.2095-1493.2021.07.00110.3969/j.issn.2095-1493.2021.07.001 ↗
31. 10.1016/j.measurement.2022.11156810.1016/j.measurement.2022.111568 ↗
32. Zhang Y. Exploring the application of fiber optic sensors in Petroleum logging. Adhesion. 2021;48(10):127–131.
33. 10.3964/j.issn.1000-0593(2016)01-0283-0410.3964/j.issn.1000-0593(2016)01-0283-04 ↗
34. 10.1016/S0924-4247(02)00430-210.1016/S0924-4247(02)00430-2 ↗
35. 10.2118/136978-MS10.2118/136978-MS ↗
36. 10.13272/j.issn.1671-251x.202305009310.13272/j.issn.1671-251x.2023050093 ↗
37. Hao J, Fan Z, Li Y. Research and design of an improved beam island membrane pressure sensor. Instrument Technol Sensors. 2019;4:10–14, 19.
38. 10.11809/bqzbgcxb2019.06.02510.11809/bqzbgcxb2019.06.025 ↗
39. 10.2118/0422-0074-JPT10.2118/0422-0074-JPT ↗
40. 10.1080/1058975050020963810.1080/10589750500209638 ↗
41. 10.2118/201604-PA10.2118/201604-PA ↗
42. 10.3390/s2118604710.3390/s21186047 ↗
43. 10.1016/j.ijleo.2020.16482510.1016/j.ijleo.2020.164825 ↗
44. 10.1016/j.gete.2024.10056610.1016/j.gete.2024.100566 ↗
45. 10.1016/j.ptlrs.2023.05.00210.1016/j.ptlrs.2023.05.002 ↗
46. 10.2118/0318-0067-JPT10.2118/0318-0067-JPT ↗
47. 10.1117/12.228568810.1117/12.2285688 ↗
48. Zhang X. Application of SAGD dynamic monitoring technology in Guantao oil reservoir. Zhongwai Energy. 2020;25(2):43–49.
49. 10.2118/0323-0062-JPT10.2118/0323-0062-JPT ↗
50. 10.13921/j.cnki.issn1002-5561.2019.01.00910.13921/j.cnki.issn1002-5561.2019.01.009 ↗
51. Li H, Deng J, Feng Y, et al. Research status and development trends of oilfield tracer technology. Appl Chem. 2023;52(11):3163–3683174.
52. 10.11867/j.issn.1001-8166.2018.05.053210.11867/j.issn.1001-8166.2018.05.0532 ↗
53. 10.3969/j.issn.1004-1699.2019.09.00510.3969/j.issn.1004-1699.2019.09.005 ↗
54. 10.3863/j.issn.1674-5086.2010.01.03110.3863/j.issn.1674-5086.2010.01.031 ↗
55. 10.2118/0322-0073-JPT10.2118/0322-0073-JPT ↗
56. 10.2118/90024-PA10.2118/90024-PA ↗
57. 10.2118/0420-0064-JPT10.2118/0420-0064-JPT ↗
58. 10.2118/200786-PA10.2118/200786-PA ↗
59. 10.12316/j.issn.1674-0831.2024.03.05410.12316/j.issn.1674-0831.2024.03.054 ↗
60. 10.7538/yzk.2021.youxian.105610.7538/yzk.2021.youxian.1056 ↗
61. 10.1016/j.applthermaleng.2022.11944110.1016/j.applthermaleng.2022.119441 ↗
62. 10.2118/102106-MS10.2118/102106-MS ↗
63. 10.11113/jt.v56.90210.11113/jt.v56.902 ↗
64. 10.2118/120460-PA10.2118/120460-PA ↗
65. Shen J, Wang Z, Ma C, et al. Development and application of interwell electromagnetic oil and gas reservoir monitoring technology. Petroleum Geophys Exploration. 2014;49(1):213–224307.
66. 10.1080/10589759.2024.234469010.1080/10589759.2024.2344690 ↗
67. 10.1016/S0920-4105(03)00041-X10.1016/S0920-4105(03)00041-X ↗
68. 10.1016/j.petrol.2021.10983910.1016/j.petrol.2021.109839 ↗
69. 10.3997/2214-4609-pdb.280.iptc14701_noPW10.3997/2214-4609-pdb.280.iptc14701_noPW ↗
70. Li J. Research on the principle and method of cross well electromagnetic logging and the influence of casings on cross well electromagnetic logging. Ocean University of China Qingdao China; 2004.
71. 10.1190/image2022-3744555.110.1190/image2022-3744555.1 ↗
72. Wu Y, Mao J, Tang J, et al. Research on the influence of casing on cross well electromagnetic logging. J Northwest Univ (Nat Sci Ed). 2014;1:17–22.
73. 10.13810/j.cnki.issn.1000-7210.2017.02.02610.13810/j.cnki.issn.1000-7210.2017.02.026 ↗
74. 10.2174/187483410150801027210.2174/1874834101508010272 ↗
75. 10.1016/j.jvolgeores.2018.02.01610.1016/j.jvolgeores.2018.02.016 ↗
76. 10.1016/j.ijggc.2022.10372610.1016/j.ijggc.2022.103726 ↗
77. 10.56952/ARMA-2022-058210.56952/ARMA-2022-0582 ↗
78. 10.11720/wtyht.2021.121910.11720/wtyht.2021.1219 ↗
79. 10.12431/issn.1000-1441.2023.62.03.01510.12431/issn.1000-1441.2023.62.03.015 ↗
80. 10.1016/j.geothermics.2024.10301010.1016/j.geothermics.2024.103010 ↗
81. 10.1016/B978-0-08-102684-7.00027-310.1016/B978-0-08-102684-7.00027-3 ↗
82. 10.1016/j.geothermics.2013.10.01310.1016/j.geothermics.2013.10.013 ↗
83. 10.1016/j.egypro.2011.02.28310.1016/j.egypro.2011.02.283 ↗
84. 10.1016/j.jappgeo.2010.05.00310.1016/j.jappgeo.2010.05.003 ↗
85. 10.1016/j.jappgeo.2024.10535110.1016/j.jappgeo.2024.105351 ↗
86. Yuan S, Ji C. Results of the world’s first four-dimensional microgravity water flooding monitoring in Pradhoe Bay, Alaska. Foreign Oilfield Eng. 2007;23(2):21–23.
87. 10.2118/115028-MS10.2118/115028-MS ↗
88. 10.3997/2214-4609-pdb.151.iptc1364010.3997/2214-4609-pdb.151.iptc13640 ↗
89. 10.1190/geo2017-0212.110.1190/geo2017-0212.1 ↗
90. 10.1080/10589759.2012.69488510.1080/10589759.2012.694885 ↗
91. 10.2118/208169-MS10.2118/208169-MS ↗
92. 10.1111/j.1365-2478.2010.00904.x10.1111/j.1365-2478.2010.00904.x ↗
93. 10.1190/1.351388110.1190/1.3513881 ↗
94. 10.1190/geo2022-0223.110.1190/geo2022-0223.1 ↗
95. 10.1016/B978-0-323-96020-5.00014-510.1016/B978-0-323-96020-5.00014-5 ↗
96. 10.1016/j.marpolbul.2022.11367710.1016/j.marpolbul.2022.113677 ↗
97. 10.1016/j.coldregions.2016.02.01310.1016/j.coldregions.2016.02.013 ↗
98. 10.1016/j.enggeo.2023.10722710.1016/j.enggeo.2023.107227 ↗
99. 10.3969/j.issn.1001-1986.2021.05.02810.3969/j.issn.1001-1986.2021.05.028 ↗
100. 10.11947/j.AGCS.2022.2022022410.11947/j.AGCS.2022.20220224 ↗