FZ
F. Zhou
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7 records found
1
Journal article
(2023)
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Feng Zhou, Iraklis Giannakis, Antonios Giannopoulos, Klaus Holliger, Evert Slob
In hydrocarbon drilling, mud filtrate penetrates permeable formations and alters the pore fluid characteristics in the immediate vicinity of the borehole. Typically, the prevailing in situ pore fluids are displaced by the invading mud filtrate, which leads to gradually changing distributions of the fluid and electrical properties. Understanding this invasion process is crucial for the interpretation of logging data and associated reservoir evaluations. Conventional logging methods tend to be inadequate for this purpose as their resolution is too low. We find that invasion depth can be determined from borehole radar data using an optimized antenna configuration and time-lapse measurements. A series of parametric sensitivity analyses provide information about the effects of variations of the rock and fluid properties on the identification and extraction of borehole radar signals reflected from the invasion front. Our results suggest that by embedding the radar antennas in cavities filled with an absorbing dielectric material, it is possible to minimize the interference arising from the metal components of the logging tool. In the simulated reservoir scenario, a time-lapse measurement mode with a time interval of at least 6 h can reliably extract the radar signals reflected from the invasion front, and the proposed borehole radar has a lateral detection range from 0.15 to 1 m. A comprehensive range of parametric sensitivity analyses indicates that the signals reflected from the invasion front are principally influenced by oil viscosity, porosity, and mud and formation water salinity, as well as by molecular diffusion coefficient and cementation exponent. These properties and parameters should be carefully explored and assessed when applying borehole radar to evaluate mud invasion information in a reservoir environment.
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In hydrocarbon drilling, mud filtrate penetrates permeable formations and alters the pore fluid characteristics in the immediate vicinity of the borehole. Typically, the prevailing in situ pore fluids are displaced by the invading mud filtrate, which leads to gradually changing distributions of the fluid and electrical properties. Understanding this invasion process is crucial for the interpretation of logging data and associated reservoir evaluations. Conventional logging methods tend to be inadequate for this purpose as their resolution is too low. We find that invasion depth can be determined from borehole radar data using an optimized antenna configuration and time-lapse measurements. A series of parametric sensitivity analyses provide information about the effects of variations of the rock and fluid properties on the identification and extraction of borehole radar signals reflected from the invasion front. Our results suggest that by embedding the radar antennas in cavities filled with an absorbing dielectric material, it is possible to minimize the interference arising from the metal components of the logging tool. In the simulated reservoir scenario, a time-lapse measurement mode with a time interval of at least 6 h can reliably extract the radar signals reflected from the invasion front, and the proposed borehole radar has a lateral detection range from 0.15 to 1 m. A comprehensive range of parametric sensitivity analyses indicates that the signals reflected from the invasion front are principally influenced by oil viscosity, porosity, and mud and formation water salinity, as well as by molecular diffusion coefficient and cementation exponent. These properties and parameters should be carefully explored and assessed when applying borehole radar to evaluate mud invasion information in a reservoir environment.
In oil drilling, mud filtrate penetrates into porous formations and alters the compositions and properties of the pore fluids. This disturbs the logging signals and brings errors to reservoir evaluation. Drilling and logging engineers therefore deem mud invasion as undesired and attempt to eliminate its adverse effects. However, the mud-contaminated formation carries valuable information, notably with regard to its hydraulic properties. Typically, the invasion depth critically depends on the formation porosity and permeability. Therefore, if adequately characterized, mud invasion effects could be used for reservoir evaluation. To pursue this objective, we have applied borehole radar to measure mud invasion depth considering its high radial spatial resolution compared with conventional logging tools, which then allows us to estimate the reservoir permeability based on the acquired invasion depth. We investigate the feasibility of this strategy numerically through coupled electromagnetic and fluid modeling in an oil-bearing layer drilled using freshwater-based mud. Time-lapse logging is simulated to extract the signals reflected from the invasion front, and a dual-offset downhole antenna mode enables time-to-depth conversion to determine the invasion depth. Based on drilling, coring, and logging data, a quantitative interpretation chart is established, mapping the porosity, permeability, and initial water saturation into the invasion depth. The estimated permeability is in a good agreement with the actual formation permeability. Our results therefore suggest that borehole radar has significant potential to estimate permeability through mud invasion effects.
...
In oil drilling, mud filtrate penetrates into porous formations and alters the compositions and properties of the pore fluids. This disturbs the logging signals and brings errors to reservoir evaluation. Drilling and logging engineers therefore deem mud invasion as undesired and attempt to eliminate its adverse effects. However, the mud-contaminated formation carries valuable information, notably with regard to its hydraulic properties. Typically, the invasion depth critically depends on the formation porosity and permeability. Therefore, if adequately characterized, mud invasion effects could be used for reservoir evaluation. To pursue this objective, we have applied borehole radar to measure mud invasion depth considering its high radial spatial resolution compared with conventional logging tools, which then allows us to estimate the reservoir permeability based on the acquired invasion depth. We investigate the feasibility of this strategy numerically through coupled electromagnetic and fluid modeling in an oil-bearing layer drilled using freshwater-based mud. Time-lapse logging is simulated to extract the signals reflected from the invasion front, and a dual-offset downhole antenna mode enables time-to-depth conversion to determine the invasion depth. Based on drilling, coring, and logging data, a quantitative interpretation chart is established, mapping the porosity, permeability, and initial water saturation into the invasion depth. The estimated permeability is in a good agreement with the actual formation permeability. Our results therefore suggest that borehole radar has significant potential to estimate permeability through mud invasion effects.
Ground-penetrating radar (GPR), usually working in the frequency from tens of megahertz to several gigahertz, is widely applied in mapping near-surface applications. In recent decades, GPR is frequently utilized for fluid-related applications, such as groundwater assessment, contaminant monitoring, and water-filled fracture detection, based on the principle that at these radar frequencies, electromagnetic (EM) waves are sensitive to water content. When operated from the surface, ground-penetrating radars are limited to a survey depth up to tens of meters in most soils. To further extend the detection range, borehole radar is developed by placing the GPR antennas in boreholes close to the underground targets. Different downhole survey modes, e.g. single-hole, cross-hole, and vertical radar profiling measurements, have demonstrated applicabilities for fracture detection, metal ore exploration, or water content prediction, up to a depth of a few hundred meters from the ground. Deeper GPR measurements in hydrocarbon reservoirs have been proposed. Some theoretical studies have shown that a borehole radar is expected to have the capability of mapping structures in the range of a few decimeters to ten meters away from the borehole in most reservoir environments, filling in the gap of the conventional electrical, sonic and nuclear logging methods. More attractively, GPR has a relatively high radial resolution and suits best for the downhole structure and fluid imaging. This thesis aims to explore the potential applications of GPR and assess their values in these oil industry applications. Applicability studies are carried out in the fields of well logging and monitoring of oil production. Numerical simulations are carried out, where joint multiphase flow and borehole radar modelling is established.
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Ground-penetrating radar (GPR), usually working in the frequency from tens of megahertz to several gigahertz, is widely applied in mapping near-surface applications. In recent decades, GPR is frequently utilized for fluid-related applications, such as groundwater assessment, contaminant monitoring, and water-filled fracture detection, based on the principle that at these radar frequencies, electromagnetic (EM) waves are sensitive to water content. When operated from the surface, ground-penetrating radars are limited to a survey depth up to tens of meters in most soils. To further extend the detection range, borehole radar is developed by placing the GPR antennas in boreholes close to the underground targets. Different downhole survey modes, e.g. single-hole, cross-hole, and vertical radar profiling measurements, have demonstrated applicabilities for fracture detection, metal ore exploration, or water content prediction, up to a depth of a few hundred meters from the ground. Deeper GPR measurements in hydrocarbon reservoirs have been proposed. Some theoretical studies have shown that a borehole radar is expected to have the capability of mapping structures in the range of a few decimeters to ten meters away from the borehole in most reservoir environments, filling in the gap of the conventional electrical, sonic and nuclear logging methods. More attractively, GPR has a relatively high radial resolution and suits best for the downhole structure and fluid imaging. This thesis aims to explore the potential applications of GPR and assess their values in these oil industry applications. Applicability studies are carried out in the fields of well logging and monitoring of oil production. Numerical simulations are carried out, where joint multiphase flow and borehole radar modelling is established.
Poster
(2019)
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Feng Zhou, Xiangyun Hu, Iraklis Giannakis, Antonios Giannopoulos, Klaus Holliger, Evert Slob
In the phase of oil drilling, mud filtrate penetrates into porous formations and alters the pore fluid properties. This complicates well logging exploration, and inevitably gives rise to shift in reservoir estimation. Logging engineers deem mud invasion a harm and attempt to eliminate its impact on logging data exploration. However, from our point of view, the mudcontaminated parts of the formation do also carry some valuable information, notably with regard to the key hydraulic properties. Therefore, if adequately characterized, mud invasion effects, in turn, could be utilized for reservoir estimation. Typically, the invasion depth critically depends on the formation porosity and permeability. To achieve this objective, we propose to use borehole radar to determine the mud invasion depth considering a high spatial resolution of ground-penetrating radar (GPR) compared with the conventional logging tools. We implement numerical investigations on the feasibility of this approach by coupling electromagnetic (EM) modelling with fluid flow modelling in an oil-bearing formation disturbed by mud invasion effects. The simulations imply that a time-lapse radar logging is able to extract EM reflection signals from mud invasion front, and the invasion depth and EM velocity can be obtained by a downhole antenna displacement of one source and two receivers. We find that there exists a positive correlation between the estimated invasion depth and permeability curves, and a negative correlation between the estimated velocity and porosity curves. We suggest that borehole radar has potential to estimate permeability and porosity of oil reservoirs, wherein the mud invasion effect is positively utilized. The study demonstrates a potential method of oil reservoir estimation and a novel application of GPR in oil fields
...
In the phase of oil drilling, mud filtrate penetrates into porous formations and alters the pore fluid properties. This complicates well logging exploration, and inevitably gives rise to shift in reservoir estimation. Logging engineers deem mud invasion a harm and attempt to eliminate its impact on logging data exploration. However, from our point of view, the mudcontaminated parts of the formation do also carry some valuable information, notably with regard to the key hydraulic properties. Therefore, if adequately characterized, mud invasion effects, in turn, could be utilized for reservoir estimation. Typically, the invasion depth critically depends on the formation porosity and permeability. To achieve this objective, we propose to use borehole radar to determine the mud invasion depth considering a high spatial resolution of ground-penetrating radar (GPR) compared with the conventional logging tools. We implement numerical investigations on the feasibility of this approach by coupling electromagnetic (EM) modelling with fluid flow modelling in an oil-bearing formation disturbed by mud invasion effects. The simulations imply that a time-lapse radar logging is able to extract EM reflection signals from mud invasion front, and the invasion depth and EM velocity can be obtained by a downhole antenna displacement of one source and two receivers. We find that there exists a positive correlation between the estimated invasion depth and permeability curves, and a negative correlation between the estimated velocity and porosity curves. We suggest that borehole radar has potential to estimate permeability and porosity of oil reservoirs, wherein the mud invasion effect is positively utilized. The study demonstrates a potential method of oil reservoir estimation and a novel application of GPR in oil fields
Reservoir monitoring using borehole radars to improve oil recovery
Suggestions from 3D electromagnetic and fluid modeling
The recently developed smart well technology allows for sectionalized production control by means of downhole inflow control valves and monitoring devices. We consider borehole radars as permanently installed downhole sensors to monitor fluid evolution in reservoirs, and it provides the possibility to support a proactive control for smart well production. To investigate the potential of borehole radar on monitoring reservoirs, we establish a 3D numerical model by coupling electromagnetic propagation and multiphase flow modeling in a bottom-water drive reservoir environment. Simulation results indicate that time-lapse downhole radar measurements can capture the evolution of water and oil distributions in the proximity (order of meters) of a production well, and reservoir imaging with an array of downhole radars successfully reconstructs the profile of a flowing water front. With the information of reservoir dynamics, a proactive control procedure with smart well production is conducted. This method observably delays the water breakthrough and extends the water-free recovery period. To assess the potential benefits that borehole radar brings to hydrocarbon recovery, three production strategies are simulated in a thin oil rim reservoir scenario, i.e., a conventional well production, a reactive production, and a combined production supported by borehole radar monitoring. Relative to the reactive strategy, the combined strategy further reduces cumulative water production by 66.89%, 1.75%, and 0.45% whereas it increases cumulative oil production by 4.76%, 0.57%, and 0.31%, in the production periods of 1 year, 5 years, and 10 years, respectively. The quantitative comparisons reflect that the combined production strategy has the capability of accelerating oil production and suppressing water production, especially in the early stage of production. We suggest that borehole radar is a promising reservoir monitoring technology, and it has the potential to improve oil recovery efficiency.
...
The recently developed smart well technology allows for sectionalized production control by means of downhole inflow control valves and monitoring devices. We consider borehole radars as permanently installed downhole sensors to monitor fluid evolution in reservoirs, and it provides the possibility to support a proactive control for smart well production. To investigate the potential of borehole radar on monitoring reservoirs, we establish a 3D numerical model by coupling electromagnetic propagation and multiphase flow modeling in a bottom-water drive reservoir environment. Simulation results indicate that time-lapse downhole radar measurements can capture the evolution of water and oil distributions in the proximity (order of meters) of a production well, and reservoir imaging with an array of downhole radars successfully reconstructs the profile of a flowing water front. With the information of reservoir dynamics, a proactive control procedure with smart well production is conducted. This method observably delays the water breakthrough and extends the water-free recovery period. To assess the potential benefits that borehole radar brings to hydrocarbon recovery, three production strategies are simulated in a thin oil rim reservoir scenario, i.e., a conventional well production, a reactive production, and a combined production supported by borehole radar monitoring. Relative to the reactive strategy, the combined strategy further reduces cumulative water production by 66.89%, 1.75%, and 0.45% whereas it increases cumulative oil production by 4.76%, 0.57%, and 0.31%, in the production periods of 1 year, 5 years, and 10 years, respectively. The quantitative comparisons reflect that the combined production strategy has the capability of accelerating oil production and suppressing water production, especially in the early stage of production. We suggest that borehole radar is a promising reservoir monitoring technology, and it has the potential to improve oil recovery efficiency.
During drilling, the mud column sustains a slightly higher pressure than the formation to maintain the stability of the well wall, which causes the mud filtrate to penetrate into formation pores and displace in-situ fluids. The invasion depth is affected by reservoir properties, especially the reservoir permeability. Therefore, it is possible to estimate the reservoir permeability if the invasion depth can be measured. A numerical study was conducted to investigate the feasibility of evaluating reservoir permeability with array induction logging. A mud invasion model was built up by coupling mud cake growth with multiple-phase fluid flow ,and an array induction logging model was established based on the Born geometric factor theory. Joint forward simulations of mud invasion and array induction logging indicated that the responses of array induction logging can reflect the effect of mud invasion on the formation resistivity. Inversion based on the damped least square method revealed that the invasion depth can be acquired from array induction logging data. We investigated the association between reservoir permeability and invasion depth, and found that in a reservoir with a permeability of 1 to 100mD(1 mD= 0.987×10-3μm～2),the reservoir permeability governs the invasion depth, and thus the permeability can be evaluated according to invasion depth. A two-dimensional numerical simulation showed that the inversed invasion depth curve had a similar fluctuation to the permeability variation. For a layered formation, a series of interpretation charts can be produced to evaluate the permeability of every layer with tolerable errors. The numerical investigation proves the feasibility of estimating reservoir permeability with array induction logging.
...
During drilling, the mud column sustains a slightly higher pressure than the formation to maintain the stability of the well wall, which causes the mud filtrate to penetrate into formation pores and displace in-situ fluids. The invasion depth is affected by reservoir properties, especially the reservoir permeability. Therefore, it is possible to estimate the reservoir permeability if the invasion depth can be measured. A numerical study was conducted to investigate the feasibility of evaluating reservoir permeability with array induction logging. A mud invasion model was built up by coupling mud cake growth with multiple-phase fluid flow ,and an array induction logging model was established based on the Born geometric factor theory. Joint forward simulations of mud invasion and array induction logging indicated that the responses of array induction logging can reflect the effect of mud invasion on the formation resistivity. Inversion based on the damped least square method revealed that the invasion depth can be acquired from array induction logging data. We investigated the association between reservoir permeability and invasion depth, and found that in a reservoir with a permeability of 1 to 100mD(1 mD= 0.987×10-3μm～2),the reservoir permeability governs the invasion depth, and thus the permeability can be evaluated according to invasion depth. A two-dimensional numerical simulation showed that the inversed invasion depth curve had a similar fluctuation to the permeability variation. For a layered formation, a series of interpretation charts can be produced to evaluate the permeability of every layer with tolerable errors. The numerical investigation proves the feasibility of estimating reservoir permeability with array induction logging.