2019
DOI: 10.3390/app9030417
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Fiber Optic Sensing for Geomechanical Monitoring: (2)- Distributed Strain Measurements at a Pumping Test and Geomechanical Modeling of Deformation of Reservoir Rocks

Abstract: In this study distributed fiber optic sensing has been used to measure strain along a vertical well of a depth of 300 m during a pumping test. The observed strain data has been used in geomechanical simulation, in which a combined analytical and numerical approach was applied in providing scaled-up formation properties. The outcomes of the field test have demonstrated the practical use of distributed fiber optic strain sensing for monitoring reservoir formation responses at different regions of sandstone–mudst… Show more

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Cited by 23 publications
(20 citation statements)
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“…Thus, fluid production or injection alters the stress field of injected formations and causes strain changes, which are sensed effectively with the DFOS technology. This proves the applicability of DFOS for monitoring reservoir formation responses at different near‐wellbore regions in a manner consistent with previous field testing work (Lei et al, ; Xue et al, ). Furthermore, in conjunction with the time‐dependent resistivity logs of MW #1 and IW #2, it is deduced that small‐scale heterogeneity and discontinuities in the formations can lead to strain changes and vertical expansion of the impacted zones.…”
Section: Resultssupporting
confidence: 89%
See 1 more Smart Citation
“…Thus, fluid production or injection alters the stress field of injected formations and causes strain changes, which are sensed effectively with the DFOS technology. This proves the applicability of DFOS for monitoring reservoir formation responses at different near‐wellbore regions in a manner consistent with previous field testing work (Lei et al, ; Xue et al, ). Furthermore, in conjunction with the time‐dependent resistivity logs of MW #1 and IW #2, it is deduced that small‐scale heterogeneity and discontinuities in the formations can lead to strain changes and vertical expansion of the impacted zones.…”
Section: Resultssupporting
confidence: 89%
“…The model was set up on the basis of an axisymmetric horizontal layered model with a geometric size of 300 × 300 × 300 m, and the temperature of the upper boundary is corresponded to 10°C with a geothermal gradient of 3°C/100 m. Normal displacement for the other boundaries is set to zero in thermal isolation and with no flow, and the major model parameters are listed in Table . Practically, the numerical model in the study constitutes part of the model used in Lei et al (). For sections ① and ②, injection scenarios were uniformly distributed amongst the grid cells corresponding to the sandy layers adjacent to the IW.…”
Section: Resultsmentioning
confidence: 99%
“…In the hydromechanical model, we set one‐dimensional layered variations (with a length interval of 1 m) of permeability ( k ) and compressibility (Cα), which are considered as the reciprocal of bulk modulus, within the ROI along the vertical direction. Following Lei et al., (2019), we applied uniform porosity ( ϕ = 0.43), Biot's coefficient ( α = 1), water compressibility (Cf = 4.5 × 10 −10 1/Pa), and Poisson's ratio (υ = 0.29) for all modeling. Only isotropic permeability and compressibility were considered.…”
Section: From Strain To Hydraulic Parameters: Forward and Inverse Modelsmentioning
confidence: 99%
“…DTS data have been useful for understanding fluid flow behavior (such as flow rate and active fluid flow zone) and reservoir characteristics owing to the hydrothermal coupling in addition to heat transport monitoring (Bense et al, 2016;Freifeld et al, 2008;Luo et al, 2020;Maldaner et al, 2019;des Tombe et al, 2019). DAS has been intensively developed and used to monitor the surface, subsurface shallow reservoirs, or deep structures (Daley et al, 2013;Jousset et al, 2018;Lellouch et al, 2019;Lindsey et al, 2019Lindsey et al, , 2020Zhu and Stensrud, 2019). On the other hand, the usage of distributed strain sensing (DSS) for subsurface monitoring of quasi-static deformation is comparatively less.…”
Section: Introductionmentioning
confidence: 99%