north western qom, iran aquifer characterization br snmr

نویسندگان

بهمن عباسی

دانشجوی کارشناسی ارشد ژئوفیزیک، گروه فیزیک زمین، مؤسسة ژئوفیزیک، دانشگاه تهران، ایران محمد کاظم حفیظی

دانشیار، گروه فیزیک زمین، مؤسسة ژئوفیزیک، دانشگاه تهران، ایران

چکیده

the objective of this research is to represent applicability of surface nuclear magnetic resonance (snmr) in aquifer characterization, based on snmr and electrical resistivity tomography data. snmr is the only geophysical method that directly detects water. two important parameters, porosity and permeability are available through inversion of initial amplitude and decay time constant versus pulse moments. usually, electrical methods are concurrently applied along with snmr surveys, making it possible to easily manipulate snmr inversion. a case study is introduced to explain the efficiency of snmr for aquifer characterizations. introduction: surface nuclear magnetic resonance (snmr) is a new geophysical method currently developed for shallow investigations of aquifers. compared to the other geophysical methods, snmr is a water selective method. therefore, hydraulic properties of media are achievable through snmr investigations. relative to classical electrical methods, snmr still costs much. in order to reduce the expense of the survey, it would be better to perform a sufficient electrical tomography in the region, and then few snmr soundings for acquiring aquifer properties. basically, in snmr the response of excited protons is measured as relaxation times in the water content (directly linked to saturated effective porosity) and pore size distribution (linked to permeability). hydrogen nuclei have a magnetic moment and in an undisturbed manner press about the ambient geomagnetic field vector (legchenko, et al., 2002). the resonance frequency ( ) is known as larmor frequency and is proportional to the strength of the earth’s magnetic field : (1) where, is the gyromagnetic ratio for hydrogen nuclei. an snmr measurement is made by disturbing protons with a secondary magnetic field ( ) transmitted at the resonant frequency ( ? ) that causes proton spinning vector ( ) to simultaneously tip away from its equilibrium and rotate about at the resonant frequency. in snmr, is applied as an alternating magnetic field with a circular or square loop as transmitter at the surface. the loop is energized by a pulse of an alternating current : (2) the degree to which m is tipped is dependent on the transmitter pulse moment q, which is the product of the transmitter current and the duration of the pulse excitation ( ).the voltage induced in the receiver loop after transmitting a certain pulse moment q is fitted with a function of the form: (3) where = initial signal amplitude; = the decay time constant; = larmor frequency as equation 1; = phase shift between the signal and the excitation current. in 1d distribution of the subsurface, the initial amplitude is a function of q: (4) the water content distribution is related to the sounding curve . the magnetic induction field of excitation is defined in the kernel function , which is linked with the loop configuration. the excitation field can be varied by changing the pulse moment q. an increase of q leads to an snmr response from deeper regions. the inverse problem to obtain the one-dimensional water content distribution can be solved in different ways, which are discussed in several snmr publications. the sounding curve is available after fitting and extrapolating the envelopes of the response signals at the several pulse moments. commonly a non-linear least square algorithm estimates the signal parameters , and . the two parameters obtained as a result of geophysical inversion are free water content, which is porosity in a saturated aquifer ( ), determined from e0, and permeability revealed from inversion (k). discussion and conclusion: the study area is located north-west of qom, iran. thirteen vertical electrical soundings in three profiles and three magnetic resonance soundings are performed over recent river deposits of the area. the studies revealed a fractured aquifer containing a low permeable shallow reservoir with high porosity and a fractured deep permeable one with low porosities. fractured aquifers, due to bad sorting of their sediments, have usually low porosities and high permabilities. an electrical tomography also shows a distinct fractured pattern in a low porosity, high permeable zone, with low amount of resistivity, which is an indication of clay accumulation in the crush zone. joint application of snmr and electrical resistivity methods are important in direct characterization of aquifer parameters including porosity, permeability and electrical resistivity. it is possible to study the relationship between electrical resistivities and porosity/permeability of the aquifer. in this study, qualitative interpretation shows an inverse relationship between electrical resistivity and porosity of the aquifer on the one side, and permeability on the other. another suggestible approach, which is currently under study, is to explore the complex relationships in a quantitative way, such as using nature inspired algorithms, like neural network estimations.

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عنوان ژورنال:
فیزیک زمین و فضا

جلد ۳۷، شماره ۱، صفحات ۰-۰

کلمات کلیدی
the objective of this research is to represent applicability of surface nuclear magnetic resonance (snmr) in aquifer characterization based on snmr and electrical resistivity tomography data. snmr is the only geophysical method that directly detects water. two important parameters porosity and permeability are available through inversion of initial amplitude and decay time constant versus pulse moments. usually electrical methods are concurrently applied along with snmr surveys making it possible to easily manipulate snmr inversion. a case study is introduced to explain the efficiency of snmr for aquifer characterizations. introduction: surface nuclear magnetic resonance (snmr) is a new geophysical method currently developed for shallow investigations of aquifers. compared to the other geophysical methods snmr is a water selective method. therefore hydraulic properties of media are achievable through snmr investigations. relative to classical electrical methods snmr still costs much. in order to reduce the expense of the survey it would be better to perform a sufficient electrical tomography in the region and then few snmr soundings for acquiring aquifer properties. basically in snmr the response of excited protons is measured as relaxation times in the water content (directly linked to saturated effective porosity) and pore size distribution (linked to permeability). hydrogen nuclei have a magnetic moment and in an undisturbed manner press about the ambient geomagnetic field vector (legchenko et al. 2002). the resonance frequency ( ) is known as larmor frequency and is proportional to the strength of the earth’s magnetic field : (1) where is the gyromagnetic ratio for hydrogen nuclei. an snmr measurement is made by disturbing protons with a secondary magnetic field ( ) transmitted at the resonant frequency ( ? ) that causes proton spinning vector ( ) to simultaneously tip away from its equilibrium and rotate about at the resonant frequency. in snmr is applied as an alternating magnetic field with a circular or square loop as transmitter at the surface. the loop is energized by a pulse of an alternating current : (2) the degree to which m is tipped is dependent on the transmitter pulse moment q which is the product of the transmitter current and the duration of the pulse excitation ( ).the voltage induced in the receiver loop after transmitting a certain pulse moment q is fitted with a function of the form: (3) where = initial signal amplitude; = the decay time constant; = larmor frequency as equation 1; = phase shift between the signal and the excitation current. in 1d distribution of the subsurface the initial amplitude is a function of q: (4) the water content distribution is related to the sounding curve . the magnetic induction field of excitation is defined in the kernel function which is linked with the loop configuration. the excitation field can be varied by changing the pulse moment q. an increase of q leads to an snmr response from deeper regions. the inverse problem to obtain the one dimensional water content distribution can be solved in different ways which are discussed in several snmr publications. the sounding curve is available after fitting and extrapolating the envelopes of the response signals at the several pulse moments. commonly a non linear least square algorithm estimates the signal parameters and . the two parameters obtained as a result of geophysical inversion are free water content which is porosity in a saturated aquifer ( ) determined from e0 and permeability revealed from inversion (k). discussion and conclusion: the study area is located north west of qom iran. thirteen vertical electrical soundings in three profiles and three magnetic resonance soundings are performed over recent river deposits of the area. the studies revealed a fractured aquifer containing a low permeable shallow reservoir with high porosity and a fractured deep permeable one with low porosities. fractured aquifers due to bad sorting of their sediments have usually low porosities and high permabilities. an electrical tomography also shows a distinct fractured pattern in a low porosity high permeable zone with low amount of resistivity which is an indication of clay accumulation in the crush zone. joint application of snmr and electrical resistivity methods are important in direct characterization of aquifer parameters including porosity permeability and electrical resistivity. it is possible to study the relationship between electrical resistivities and porosity/permeability of the aquifer. in this study qualitative interpretation shows an inverse relationship between electrical resistivity and porosity of the aquifer on the one side and permeability on the other. another suggestible approach which is currently under study is to explore the complex relationships in a quantitative way such as using nature inspired algorithms like neural network estimations.

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