The possibilities of monitoring the operation of gas wells by noise measurement using a system of distributed acoustic sensors
1 Perm National Research Polytechnic University, Russia 29, Komsomolsky prospect, Perm, 614990: igorek999@yandex.ru, sv.belov63@mail.ru, Nikita.Chistyakov@fxc-png.ru, shum5011@gmail.com, vaqifqurbanov@mail.ru
2 Institute of Oil and Gas, MSERA, Azerbaijan 9 Baku, F. Amirov str., Baku, AZ1000: vaqifqurbanov@mail.ru
DOI: 10.33677/ggianas20240200133
Summary
The experience of using fiber-optic distributed acoustic sensing (DAS) for spectral noise logging based on a geophysical cable when monitoring the development of a gas condensate field is considered. Studies have been carried out to assess the spectral sensitivity of the DAS method. A technique has been developed for filtering the original signal with calculation of the signal energy in various frequency ranges, which carries information about the movement of fluid inside the well. Using these methods, the moment of stopping the well is clearly identified. By combining sound logging of wells with studies based on a fiber-optic system of distributed temperature sensing (DTS), intervals of gas-saturated formations operating in the well were identified.
It has been established that the information content of the DAS and DTS systems depends on the location of the cable. For monitoring development using the DTS technology, it is optimal to place the cable inside or outside the production casing. When the cable is located inside the tubing, the temperature field is distorted by counter-current fluid flows. The sensitivity of the DAS system to noise from the rock and the production casing can also be increased by optimizing the cable location, which can be justified with a wider implementation of this technology in production.
To be able to record noise from fluid movement behind the column and in the rock, it is necessary to expand the frequency range of the recorded vibrations by using special cables with increased sensitivity and an expanded directional diagram.
Keywords: spectral noise logging, fiber optic distributed acoustic sensing, gas-saturated formations, frequency range
REFERENCES
Aslanian A.M., Aslanian I.Yu., Maslennikova Y.S. et al. Diagnostics of gas overflows by a complex of high-precision thermometry, spectral noise measurement and pulsed neutron-neutron logging. Territory of Oil and Gas, No. 6, 2016, pp. 74-81 (in Russian).
Bai X., Zhang F., Lin L. et al. Phase drift and noise suppression method based on SEE-SGMD-PCC in a distributed acoustic sensor. Optics Express, Vol. 31, No. 19, 2023, pp. 31463-31485, https://doi.org/10.1364/OE.495356.
Chen W., Ma X., Ma Q. et al. Denoising method of the φ-OTDR system based on EMD-PCC. IEEE Sensors Journal, Vol. 21, No. 10, 2021, pp. 12113-12118, DOI: 10.1109/JSEN.2020. 3033674.
Chugaev A.V., Tarantin M.V. Amplitude-frequency response of distributed acoustic sensor DAS with spiral winding of fiber. Mining Science and Technology, Vol. 8, No. 1, 2023, pp. 13-21, DOI: 10.17073/2500-0632-2022-06-10 (in Russian).
Chulkov E., Tikhotsky S.A., Dubinya N.V. Design of seismic sensors based on the DAS principle: analysis and numerical modeling. Proceedings of the International Geological and Geophysical Conference, March 27-29, 2023. Vol. 3, PolyPRESS. Tver, 2023, 234 p. (in Russian).
Daley T.M. et al. Field testing of fiber-optic distributed acoustic sensing (DAS) for subsurface seismic monitoring. The Leading Edge, Vol. 32, No. 6, 2013, pp. 699-706, DOI:10.1190/ tle32060699.1.
Dean T., Cuny T., Hartog A.H. The effect of gauge length on axially incident P-waves measured using fibre optic distributed vibration sensing: Gauge length effect on incident P-waves. Geophysical Prospecting, Vol. 65, No. 1, 2017, pp. 184-193, DOI: 10.1111/1365-2478.12419.
Gabai H., Eyal A. On the sensitivity of distributed acoustic sensing. Optics Letters, Vol. 41, No. 24, 2016, pp. 5648-5651, https://doi.org/10.1364/OL.41.005648.
Ipatov A.I. et al. Monitoring of reservoir production in horizontal wellbores based on the results of unsteady thermometry by distributed fiber-optic sensors. PRONEFT - Professionally About Oil, 2021, No. 4 (22), pp. 81-91 (in Russian).
Kislov K.V., Gravirov V.V. Distributed acoustic sounding: a new tool or a new paradigm. Seismic Instruments, Vol. 58, No. 2, 2022, p. 5-38, DOI: 10.21455/si2022.2-1.
Kolychev I.Yu., Denisov A.M., Belov S.V. et al. Assessment of possibilities of application of vibroacoustic impact technology (DAS) in monitoring of oil and gas wells operation. Problems of Development of Hydrocarbon and Ore Mineral Deposits, Vol. 1, 2022, pp. 250-255 (in Russian).
Kuvshinov B.N. Interaction of helically wound fibre-optic cables with plane seismic waves. Geophysical Prospecting, Vol. 64, No. 3, 2016, pp. 671-688, DOI: 10.1111/1365-2478.12303.
Lee D., Park K.G., Lee C.-N., Choi S.-J. Distributed temperature sensing monitoring of well completion processes in a CO2 Geological Storage Demonstration Site. Sensors, Basel, Vol. 18, No. 12, 2018, 4239 p., https://doi.org/10.3390/s18124239.
Mao B., Bu Z. Xu B. et al. Denoising method based on VMD-PCC in φ-otdr system. Optical Fiber Technology, Vol. 74, No. 3, 2022, 103081, DOI: 10.1016/j.yofte.2022.103081.
Mateeva A., Mestayer J., Cox B. et al. Advances in distributed acoustic sensing (DAS) for VSP. SEG Technical Program Expanded Abstracts, 2012, 4609 p., DOI: 10.1190/segam2012-0739.1.
Moradi P., Dande S., Angus D. Fibre-optic sensing and microseismic monitoring evaluate and enhance hydraulic fracturing via real-time and post-treatment analysis. First Break, Vol. 38, No. 9, 2020, pp. 65-72.
Näsholm S.P., Iranpour K., Wuestefeld A. et al. Array signal processing on distributed acoustic sensing data: directivity effects in slowness space. Journal of Geophysical Research: Solid Earth, Vol. 127, No. 2, 2022, pp. 1-24, DOI: 10.1029/2021JB023587.
Nikolaev S.A., Ovchinnikov M.N. Sound generation by a filtrational flow in porous. Akusticeskij zurnal, Vol. 38, No. 1, 1992, pp. 114-118 (in Russian).
Parker T., Shatalin S., Farhadiroushan M. Distributed acoustic sensing – a new tool for seismic applications. First Break, Vol. 32, No. 2, 2014, pp. 61-69, DOI: 10.3997/1365-2397. 2013034.
Stork A.L., Baird A.F., Horne S.A. et al. Application of machine learning to microseismic event detection in distributed acoustic sensing data. Geophysics, Vol. 85, No. 5, 2020, pp. 149-160, DOI: 10.1190/geo2019-0774.1.
Wu H., Li X., Li H. et al. An effective signal separation and extraction method using multi-scale wavelet decomposition for phase-sensitive OTDR system. The International Society for Optical Engineering, Vol. 8916, 2013, 89160Z, DOI: 10.1117/12.2035836.
Wu X., Willis M.E., Palacios W. et al. Compressional and shear-wave studies of distributed acoustic sensing acquired vertical seismic profile data. The Leading Edge, Vol. 36, No. 12, 2017, pp. 962-1044, DOI: 10.1190/tle36120987.1.
Zhirnov A.A., Stepanov K.V., Chernutsky A.O. et al. Influence of laser frequency drift in phase-sensitive optical time domain reflectometry. Optics and Spectroscopy. Vol. 127, No. 10, 2019, pp. 656-663, DOI: 10.21883/OS.2019.10.48364.177-19 (in Russian).
DOI: 10.33677/ggianas20240200133