Subsurface Conductivity Research Articles

Probabilistic Inversion of Multiconfiguration Electromagnetic Induction Data Using Dimensionality Reduction Technique: A Numerical Study

Core Ideas DCT‐based inversion of EMI data successfully recovers subsurface conductivity images. Training image‐based parameterization ensures accurate subsurface characterization. Using ECa data pseudosection as a training image provides an adequate prior. Low‐frequency loop–loop electromagnetic induction (EMI) offers several key advantages over many other geophysical techniques for proximal soil sensing. Yet, because of problems with the inversion of measured apparent electrical conductivity (ECa) data, application of EMI for geophysical imaging and interpretation is limited. In this study, a Bayesian inference was used to obtain electromagnetic conductivity images (EMCIs) from multiconfiguration ECa data. This approach allows analysis of highly nonlinear problems and renders an ensemble of models obtained from the posterior distribution that can be used to explore parameter uncertainty. In this respect, generalized formal likelihood function was used to more accurately describe the sensitivity of the posterior distribution to residual assumptions. Discrete cosine transform (DCT) was employed as a model compression technique to reduce the number of unknown parameters in the inversion. The DCT parameterization was performed using training image (TI)‐based geostatistical simulations considering the ECa data pseudosection as a TI. The potential of the proposed approach was examined through different theoretical scenarios. The estimated subsurface EMCI shows excellent agreement with the original synthetic models subject to the appropriate choice of prior information. Moreover, DCT parameterization reduces the number of unknown parameters, increasing accuracy of the inversion with the Bayesian procedure. The proposed approach ensures accurate and high‐resolution characterization of subsurface conductivity layering from measured ECa values.

Simultaneous calibration and inversion algorithm for multiconfiguration electromagnetic induction data acquired at multiple elevations

Electromagnetic induction (EMI) is a contactless and fast geophysical measurement technique. Frequency-domain EMI systems are available as portable rigid booms with fixed separations up to approximately 4 m between the transmitter and the receivers. These EMI systems are often used for high-resolution characterization of the upper subsurface meters (up to depths of approximately 1.5 times the maximum coil separation). The availability of multiconfiguration EMI systems, which measure multiple apparent electrical conductivity ([Formula: see text]) values of different but overlapping soil volumes, enables EMI data inversions to estimate electrical conductivity ([Formula: see text]) changes with depth. However, most EMI systems currently do not provide absolute [Formula: see text] values, but erroneous shifts occur due to calibration problems, which hinder a reliable inversion of the data. Instead of using physical soil data or additional methods to calibrate the EMI data, we have used an efficient and accurate simultaneous calibration and inversion approach to avoid a possible bias of other methods while reducing the acquisition time for the calibration. By measuring at multiple elevations above the ground surface using a multiconfiguration EMI system, we simultaneously obtain multiplicative and additive calibration factors for each coil configuration plus an inverted layered subsurface electrical conductivity model at the measuring location. Using synthetic data, we verify our approach. Experimental data from five different calibration positions along a transect line showed similar calibration results as the data obtained by more elaborate vertical electrical sounding reference measurements. The synthetic and experimental results demonstrate that the multielevation calibration and inversion approach is a promising tool for quantitative electrical conductivity analyses.

Focused attributes derived from AEM surveys using the continuous wavelet transform

Interpretation of a hydrogeophysical survey is a complex and comprehensive process. In addition to an areal coverage with AEM data, most often an interpretation involves additional data that are time consuming to collect and complicated to integrate into an overall model, e.g. borehole logs, borehole core samples, water chemistry, surface vegetation, satellite imagery plus the generally accepted geological background knowledge. Compared with the complexities of the interpretation process, the acquisition, QC and inversion of AEM survey data are a more straightforward affair and considerably less time consuming.Interpretation basically has to do with identifying categories and finding boundaries between them so that depths, thicknesses, lithologies and a whole range of other model attributes can be estimated, qualitatively and quantitatively. To supplement the traditional product delivered by the inverter to the interpreter: inversion models displaying the distribution of subsurface electrical conductivity, I present two methods based on the Continuous Wavelet Transform that can deliver more focused attributes to assist in the interpretation. In the first method, layer boundaries in the smooth multi-layer models that are most often used in the inversion of large data sets are found. In the second method, the spatial distribution of the natural categories of the model parameter is found. Both methods are based on the inversion models and, evidently, they are useful to the extent that the variations in conductivity reflect geological/hydrogeological boundaries and categories - which is for the interpreter to decide.

Uncovering the Musgrave Province in South Australia using airborne EM

Two airborne electromagnetic (AEM) surveys were undertaken in the Musgrave Province in South Australia in 2016 with the objective to increase knowledge about cover characteristics, thereby helping reduce exploration risks and to gain an understanding of the groundwater resource potential of the area. The Province is highly prospective for magmatic Ni-Cu-PGE and IOCG deposits, where a transported regolith imposes a significant challenge to exploration. Effective exploration through this region requires an understanding of that cover, its character and its spatial variability. This cover is also a source of groundwater that supports community and environment but our understanding of this resource is compromised by the limited information we have about it. Two different systems, TEMPEST and SkyTEM, were used for the survey, each covering around 8000 line km with a line spacing of 2 km. The line spacing was deliberately chosen to provide a spatially coherent picture of the subsurface conductivity structure, particularly the buried palaeovalleys known to be present in the region. The two datasets were processed and inverted and the results assessed against known information from drill holes. Both systems map the palaeovalley systems in the area well and provide information about the location and geometry of these. Furthermore the results indicate that it is possible to map variability within the cover using AEM, as well as structural controls on the orientation of the palaeovalleys. Airborne electromagnetic surveys used in logistically challenging areas can therefore be a useful mapping tool for areas with varied but unknown cover sequence thickness and thereby reducing exploration risks, as well as increasing the information content about groundwater resources.

Interpretation attributes derived from airborne electromagnetic inversion models using the continuous wavelet transform

ABSTRACTPlanning, contracting, data acquisition and processing plus the inverter's quality assessment and inversion of a regional airborne electromagnetic survey may take some months, while the interpretation of the results is a considerably more complex and comprehensive process. Most often an interpretation necessitates additional data that are time consuming to collect and complicated to integrate into an overall model, for example borehole logs, borehole core samples, water chemistry, surface vegetation, satellite imagery plus all existing geological background knowledge. Interpretation basically has to do with identifying categories and finding boundaries between them so that depths, thicknesses and a whole range of other model attributes can be estimated, qualitatively and/or quantitatively. I present two methods using the continuous wavelet transform of finding attributes intended to assist the interpreter: one finds layer boundaries in the smooth multi‐layer models that are most often used in the inversion of large airborne electromagnetic data sets, and the other finds the natural categories of the model parameter. Naturally, being based on the subsurface conductivity distribution, the boundaries and categories suggested are useful only to the extent that they coincide with geological/hydrogeological boundaries and categories – which is for the interpreter to decide.

Distributed Thermal Response Tests Using a Heating Cable and Fiber Optic Temperature Sensing

Thermal response tests are used to assess the subsurface thermal conductivity to design ground-coupled heat pump systems. Conventional tests are cumbersome and require a source of high power to heat water circulating in a pilot ground heat exchanger. An alternative test method using heating cable was verified in the field as an option to conduct this heat injection experiment with a low power source and a compact equipment. Two thermal response tests using heating cable sections and a continuous heating cable were performed in two experimental heat exchangers on different sites in Canada and France. The temperature evolution during the tests was monitored using submersible sensors and fiber optic distributed temperature sensing. Free convection that can occur in the pipe of the heat exchanger was evaluated using the Rayleigh number stability criterion. The finite and infinite line source equations were used to reproduce temperature variations along the heating cable sections and continuous heating cable, respectively. The thermal conductivity profile of each site was inferred and the uncertainly of the test was evaluated. A mean thermal conductivity 15% higher than that revealed with the conventional test was estimated with heating cable sections. The thermal conductivity evaluated using the continuous heating cable corresponds to the value estimated during the conventional test. The average uncertainly associated with the heating cable section test was 15.18%, while an uncertainty of 2.14% was estimated for the test with the continuous heating cable. According to the Rayleigh number stability criterion, significant free convection can occur during the heat injection period when heating cable sections are used. The continuous heating cable with a low power source is a promising method to perform thermal response tests and further tests could be carried out in deep boreholes to verify its applicability.

Groundwater Controls on Postfire Permafrost Thaw: Water and Energy Balance Effects

AbstractFire frequency and severity are increasing in high‐latitude regions, but the degree to which groundwater flow impacts the response of permafrost to fire remains poorly understood. Here we use the Anaktuvuk River Fire (Alaska, USA) as an example for simulating groundwater‐permafrost interactions following fire. We identify key thermal and hydrologic parameters controlling permafrost response to fire both with and without groundwater flow, and separate the relative influence of changes to the water and energy balances on active layer thickness. Our results show that mineral soil porosity, which influences the bulk subsurface thermal conductivity, is a key parameter controlling active layer response to fire in both the absence and presence of groundwater flow. However, including groundwater flow in models increases the perceived importance of subsurface hydrologic properties, such as the soil permeability, and decreases the perceived importance of subsurface thermal properties, such as the thermal conductivity of soil solids. Furthermore, we demonstrate that changes to the energy balance (increased soil temperature) drive increased active layer thickness following fire, while changes to the water balance (decreased groundwater recharge) lead to reduced landscape‐scale variability in active layer thickness and groundwater discharge to surface water features such as streams. These results indicate that explicit consideration of groundwater flow is critical to understanding how permafrost environments respond to fire.

Colloquium 2016: Assessment of subsurface thermal conductivity for geothermal applications

The construction of “green” buildings using geothermal energy requires knowledge of the ground thermal conductivity, assessed when designing the heating and cooling system of commercial buildings with ground-coupled heat pumps. The most commonly used method for active field assessment is the thermal response test (TRT), which consists of circulating heated water in a pilot ground heat exchanger (GHE) where temperature and flow rate are monitored. The transient thermal perturbation is analyzed to evaluate the subsurface thermal conductivity. Heat injection can also be performed with a heating cable in the GHE to conduct a TRT without water circulation, which can be affected by surface temperature variations. Passive methods, such as the interpretation of geophysical well logs and the analysis of temperature profiles measured in exploration wells, are emerging as alternatives to TRTs. Steady-state and transient laboratory measurements performed on samples collected in surface outcrops or drill cores can also be achieved. Methods to characterize the subsurface in the context of geothermal system design have evolved significantly since the original TRT concept proposed during the 1980s with different techniques inspired from the Earth science sector.

A new far‐field low‐frequency electromagnetic method for measurement of temporal variations in subsurface electrical conductivity averaged over a transect

ABSTRACTThe new far‐field low‐frequency electromagnetic method used the electromagnetic ground wave from distant radio transmitters at low frequencies to estimate temporal variations of factors affecting subsurface electrical conductivity averaged along the propagation path between either a transmitter and a receiver or two receivers that are in line with a transmitter. Phase and phase difference between two receivers depend on three factors that influence the changes in electrical conductivity: soil moisture, depth to the groundwater table and soil temperature. This dependence was investigated by simulations and evaluated by an experiment. The measurement layout was based on simulating ground wave propagation over a layered subsurface using the surface impedance method and the Sommerfeld ground wave attenuation function. A three‐layer model for the subsurface was used, which includes a soil layer, an unsaturated vadose zone and a saturated groundwater zone. The results of simulations at a frequency of 77.5 kHz showed that the phase of the ground wave is strongly influenced by natural variation of the above‐mentioned three factors; 77.5 kHz is the carrier frequency of the Normal Time Service Germany (DCF77) in Mainflingen/Germany, that was chosen as a source of the low‐frequency radio waves used in the experiment. Over a 2‐year measurement period, the amplitude and phase of the ground wave were recorded with two receivers, one 70 km and the other 110 km away from the transmitter. Additionally, phase difference between the two receivers was calculated. In situ observations of soil moisture, depth to the groundwater table, and soil temperature along the transects under investigation were used to estimate phase and phase difference dependencies. Multiple regression analysis of the measured phase and phase difference revealed a strong dependence on the depth to the groundwater table and on soil temperature, whereas the impact of soil moisture on the phase and phase difference was found to be very low. Conversely, the relations obtained can be used to estimate the variation of the depth to the groundwater table, if the phase at a given frequency and the soil temperature information are available.

A Comparison of Model‐Based Ionospheric and Ocean Tidal Magnetic Signals With Observatory Data

AbstractObserved tidal geomagnetic field variations are due to a combination of electric currents in the ionosphere, ocean, and their induced counterparts. Using these variations to constrain subsurface electrical conductivity in oceanic regions is a promising frontier; however, properly separating the ionospheric and oceanic tidal contributions of the magnetic field is critical for this. We compare semidiurnal lunar tidal magnetic signals (i.e., the signals due to the M2 tidal mode) estimated from 64 global observatories to physics‐based forward models of the ionospheric M2 magnetic field and the oceanic M2 magnetic field. At ground level, predicted ionospheric M2 amplitudes are strongest in the horizontal components, whereas the predicted oceanic amplitudes are strongest in the vertical direction. There is good agreement between the predicted and estimated M2 phases for the Y component; however, the F and X components experience deviations that may be indicative of unmodeled ionospheric processes or unmodeled coastal effects. Overall, we find that the agreement between the physics‐based model predictions and the observations is very encouraging for electromagnetic sensing applications, especially since the predicted ionospheric vertical component is very weak.

A novel hybrid approach for in-situ determining the thermal properties of subsurface layers around borehole heat exchanger

Performance of shallow geothermal systems such as borehole thermal energy storage (BTES) and ground source heat pump (GSHP) mainly depends on the thermal properties of the subsurface and proper design of borehole heat exchangers (BHE). This paper introduces a novel hybrid approach for measuring the effectiveness of BHEs and surrounding subsurface thermal properties, which combines traditional thermal response test (TRT) with the borehole temperature relaxation method (BTR), based on two dimensional radial conductive heat transfer. The new method allows for: (1) evaluation of how convective heat loss at groundwater layers influence estimation of subsurface thermal properties; (2) examination of non-uniform heat transfer through a BHE to stratified subsurface layers; and, (3) calculation of depth-dependency of thermal properties of unsaturated subsurface layers. The hybrid approach was tested using a 50 m U-type BHE, the results of which indicated that convective heat transfer at the groundwater level altered the real value of effective thermal conductivity from 0.45 to 1.56 W/m K. The non-uniformity of heat transfer along the BHE was confirmed by calculations that showed subsurface thermal conductivities were depth dependent, varying between 0.34 and 0.61 W/m K.

Bridging the gap between numerical solutions of travel time distributions and analytical storage selection functions

AbstractRecent advancements in analytical solutions to quantify water and solute travel time distributions (TTDs) and the related StorAge Selection (SAS) functions synthesize catchment complexity into a simplified, lumped representation. Although these analytical approaches are efficient in application, they require rarely available long‐term and high‐frequency hydrochemical data for parameter estimation. Alternatively, integrated hydrologic models coupled to Lagrangian particle‐tracking approaches can directly simulate age under different catchment geometries and complexity, but at a greater computational expense. Here, we bridge the two approaches, using a physically based model to explore the uncertainty in the estimation of the SAS function shape. In particular, we study the influence of subsurface heterogeneity, interactions between distinct flow domains (i.e., the vadose zone and saturated groundwater), diversity of flow pathways, and recharge rate on the shape of TTDs and the SAS functions. We use an integrated hydrology model, ParFlow, linked with a particle‐tracking model, SLIM, to compute transient residence times (or ages) at every cell in the domain, facilitating a direct characterization of the SAS function. Steady‐state results reveal that the SAS function shape shows a wide range of variation with respect to the variability in the structure of subsurface heterogeneity. Ensembles of spatially correlated realizations of hydraulic conductivity indicate that the SAS functions in the saturated groundwater have an overall weak tendency toward sampling younger ages, whereas the vadose zone gives a strong preference for older ages. We further show that the influence of recharge rate on the TTD is tightly dependent on the variability of subsurface hydraulic conductivity.

3D electrical conductivity tomography of volcanoes

Electrical conductivity tomography is a well-established galvanometric method for imaging the subsurface electrical conductivity distribution. We characterize the conductivity distribution of a set of volcanic structures that are different in terms of activity and morphology. For that purpose, we developed a large-scale inversion code named ECT-3D aimed at handling complex topographical effects like those encountered in volcanic areas. In addition, ECT-3D offers the possibility of using as input data the two components of the electrical field recorded at independent stations. Without prior information, a Gauss-Newton method with roughness constraints is used to solve the inverse problem. The roughening operator used to impose constraints is computed on unstructured tetrahedral elements to map complex geometries. We first benchmark ECT-3D on two synthetic tests. A first test using the topography of Mt. St Helens volcano (Washington, USA) demonstrates that we can successfully reconstruct the electrical conductivity field of an edifice marked by a strong topography and strong variations in the resistivity distribution. A second case study is used to demonstrate the versatility of the code in using the two components of the electrical field recorded on independent stations along the ground surface. Then, we apply our code to real data sets recorded at (i) a thermally active area of Yellowstone caldera (Wyoming, USA), (ii) a monogenetic dome on Furnas volcano (the Azores, Portugal), and (iii) the upper portion of the caldera of Kīlauea (Hawai'i, USA). The tomographies reveal some of the major structures of these volcanoes as well as identifying alteration associated with high surface conductivities. We also review the petrophysics underlying the interpretation of the electrical conductivity of fresh and altered volcanic rocks and molten rocks to show that electrical conductivity tomography cannot be used as a stand-alone technique due to the non-uniqueness in interpreting electrical conductivity tomograms. That said, new experimental data provide evidence regarding the strong role of alteration in the vicinity of preferential fluid flow paths including magmatic conduits and hydrothermal vents.

An adaptive Gaussian process-based iterative ensemble smoother for data assimilation

Abstract Accurate characterization of subsurface hydraulic conductivity is vital for modeling of subsurface flow and transport. The iterative ensemble smoother (IES) has been proposed to estimate the heterogeneous parameter field. As a Monte Carlo-based method, IES requires a relatively large ensemble size to guarantee its performance. To improve the computational efficiency, we propose an adaptive Gaussian process (GP)-based iterative ensemble smoother (GPIES) in this study. At each iteration, the GP surrogate is adaptively refined by adding a few new base points chosen from the updated parameter realizations. Then the sensitivity information between model parameters and measurements is calculated from a large number of realizations generated by the GP surrogate with virtually no computational cost. Since the original model evaluations are only required for base points, whose number is much smaller than the ensemble size, the computational cost is significantly reduced. The applicability of GPIES in estimating heterogeneous conductivity is evaluated by the saturated and unsaturated flow problems, respectively. Without sacrificing estimation accuracy, GPIES achieves about an order of magnitude of speed-up compared with the standard IES. Although subsurface flow problems are considered in this study, the proposed method can be equally applied to other hydrological models.

Inverts permittivity and conductivity with structural constraint in GPR FWI based on truncated Newton method

Full waveform inversion (FWI) of ground penetrating radar (GPR) is a promising technique to quantitatively evaluate the permittivity and conductivity of near subsurface. However, these two parameters are simultaneously inverted in the GPR FWI, increasing the difficulty to obtain accurate inversion results for both parameters. In this study, I present a structural constrained GPR FWI procedure to jointly invert the two parameters, aiming to force a structural relationship between permittivity and conductivity in the process of model reconstruction. The structural constraint is enforced by a cross-gradient function. In this procedure, the permittivity and conductivity models are inverted alternately at each iteration and updated with hierarchical frequency components in the frequency domain. The joint inverse problem is solved by the truncated Newton method which considering the effect of Hessian operator and using the approximated solution of Newton equation to be the perturbation model in the updating process. The joint inversion procedure is tested by three synthetic examples. The results show that jointly inverting permittivity and conductivity in GPR FWI effectively increases the structural similarities between the two parameters, corrects the structures of parameter models, and significantly improves the accuracy of conductivity model, resulting in a better inversion result than the individual inversion.

Low signal-to-noise FDEM in-phase data: Practical potential for magnetic susceptibility modelling

In this paper, we consider the use of land-based frequency-domain electromagnetics (FDEM) for magnetic susceptibility modelling. FDEM data comprises both out-of-phase and in-phase components, which can be related to the electrical conductivity and magnetic susceptibility of the subsurface. Though applying the FDEM method to obtain information on the subsurface conductivity is well established in various domains (e.g. through the low induction number approximation of subsurface apparent conductivity), the potential for susceptibility mapping is often overlooked. Especially given a subsurface with a low magnetite and maghemite content (e.g. most sedimentary environments), it is generally assumed that susceptibility is negligible. Nonetheless, the heterogeneity of the near surface and the impact of anthropogenic disturbances on the soil can cause sufficient variation in susceptibility for it to be detectable in a repeatable way. Unfortunately, it can be challenging to study the potential for susceptibility mapping due to systematic errors, an often poor low signal-to-noise ratio, and the intricacy of correlating in-phase responses with subsurface susceptibility and conductivity. Alongside use of an accurate forward model – accounting for out-of-phase/in-phase coupling – any attempt at relating the in-phase response with subsurface susceptibility requires overcoming instrument-specific limitations that burden the real-world application of FDEM susceptibility mapping. Firstly, the often erratic and drift-sensitive nature of in-phase responses calls for relative data levelling. In addition, a correction for absolute levelling offsets may be equally necessary: ancillary (subsurface) susceptibility data can be used to assess the importance of absolute in-phase calibration though hereby accurate in-situ data is required. To allow assessing the (importance of) in-phase calibration alongside the potential of FDEM data for susceptibility modelling, we consider an experimental test case whereby the in-phase responses of a multi-receiver FDEM instrument are calibrated through downhole susceptibility data. Our results show that, while it is possible to derive approximate susceptibility profiles from FDEM data, robust quantitative analysis hinges on appropriate calibration of the responses.

Thermal conductivity of lunar regolith simulant JSC-1A under vacuum

Many air-less planetary bodies, including the Moon, asteroids, and comets, are covered by regolith. The thermal conductivity of the regolith is an essential parameter controlling the surface temperature variation. A thermal conductivity model applicable to natural soils as well as planetary surface regolith is required to analyze infrared remote sensing data. In this study, we investigated the temperature and compressional stress dependence of the thermal conductivity of the lunar regolith simulant JSC-1A, and the temperature dependence of sieved JSC-1A samples under vacuum conditions. We confirmed that a series of the experimental data for JSC-1A are fitted well by our analytical model of the thermal conductivity (Sakatani et al., 2017). Comparison with the calibration data of the sieved samples with those for original JSC-1A indicates that the thermal conductivity of natural samples with a wide grain size distribution can be modeled as mono-sized grains with a volumetric median size. The calibrated model can be used to estimate the volumetric median grain size from infrared remote sensing data. Our experiments and the calibrated model indicates that uncompressed JSC-1A has similar thermal conductivity to lunar top-surface materials, but the lunar subsurface thermal conductivity cannot be explained only by the effects of the density and self-weighted compressional stress. We infer that the nature of the lunar subsurface regolith grains is much different from JSC-1A and lunar top-surface regolith, and/or the lunar subsurface regolith is over-consolidated and the compressional stress higher than the hydrostatic pressure is stored in the lunar regolith layer.

A computationally efficient numerical model for heat transfer simulation of deep borehole heat exchangers

Being a promising technique for seasonal thermal energy storage, the deep borehole heat exchanger (DBHE) has also provided a new variance of ground-coupled heat pump systems especially for applications in cold-climate regions. Numerical simulations are recognized as the appropriate means in the study on heat transfer around the deep boreholes, which often features time-consuming computations. A model has been established in this study for DBHEs with coaxial tubes, considering coupled heat transfer in the tubes and surrounding subsurface. A software package is developed based on the finite difference method for thermal analysis of the DBHEs, and an algorithm for direct solution of resulted algebraic equation set is used so as to achieve very efficient computation. The model and the numerical algorithm are validated by comparison with simulation results from a reference using the finite element method. Performance of DBHEs is then assessed with parameter analyses. A diagram is presented to show relations of the nominal DBHE capacity to its key parameters such as the borehole depth, geothermal heat flux and thermal conductivity of subsurface, which is helpful in engineering practice. Studies also indicate that a high-resistance inner pipe helps in improving the heat transfer capacity of DBHEs.

Lithospheric electrical structure of the middle Lhasa terrane in the south Tibetan plateau

The Lhasa terrane in southern Tibetan plateau is a huge tectono-magmatic belt and an important metallogenic belt. Its formation evolution process and mineralization are affected by the subduction of oceanic plate and subsequent continental collision. However, the evolution of Lhasa terrane has been a subject of much debate for a long time. The Lithospheric structure records the deep processes of the subduction of oceanic plate and continental collision. The magnetotelluric (MT) method can probe the sub-surface electrical conductivity, newly dense broadband and long period magnetotelluric data were collected along a south-north trending profile that across the Lhasa terrane at 88°–89°E. Dimensionality analyses demonstrated that the MT data can be interpreted using two-dimensional approaches, and the regional strike direction was determined as N110°E.Based on data analysis results, a two-dimensional (2-D) resistivity model of crust and upper mantle was derived from inversion of the transverse electric mode, transverse magnetic mode and vertical magnetic field data. Inversion model shows a large north-dipping resistor that extended from the upper crust to upper mantle beneath the Himalaya and the south of Lhasa Terrane, which may represent the subducting Indian continental lithosphere. The 31°N may be an important boundary in the Lhasa Terrane, the south performs a prominent high-conductivity anomaly from the lower crust to upper mantle which indicates the existence of asthenosphere upwelling, while the north performs a higher resistivity and may have a reworking ancient basement. The formation of the ore deposits in the study area may be related to the upwelling of the mantle material triggered by slab tearing and/or breaking off of the Indian lithosphere, and the mantle material input also contributed the total thickness of the present-day Tibetan crust. The results provide helpful constrains to understand the mechanism of the continent-continent collision and the regional exploratory prospect of the deep resources.

Evaluation of the Internal and Borehole Resistances during Thermal Response Tests and Impact on Ground Heat Exchanger Design

The main parameters evaluated with a conventional thermal response test (TRT) are the subsurface thermal conductivity surrounding the borehole and the effective borehole thermal resistance, when averaging the inlet and outlet temperature of a ground heat exchanger with the arithmetic mean. This effective resistance depends on two resistances: the 2D borehole resistance (Rb) and the 2D internal resistance (Ra) which is associated to the short-circuit effect between pipes in the borehole. This paper presents a field method to evaluate these two components separately. Two approaches are proposed. In the first case, the temperature at the bottom of the borehole is measured at the same time as the inlet and outlet temperatures as done in a conventional TRT. In the second case, different flow rates are used during the experiment to infer the internal resistance. Both approaches assumed a predefined temperature profile inside the borehole. The methods were applied to real experimental tests and compared with numerical simulations. Interesting results were found by comparison with theoretical resistances calculated with the multipole method. The motivation for this work is evidenced by analyzing the impact of the internal resistance on a typical geothermal system design. It is shown to be important to know both resistance components to predict the variation of the effective resistance when the flow rate and the height of the boreholes are changed during the design process.