Case Histories

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CASE HISTORIES CONTENTS

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17.1 17.2 17.3 17.4 17.5

Tectonic Studies – EarthScope MT Survey in the Northwestern United States ........................... 683 Crustal Studies – the Khibini Experiment ....................................................................... 689 Minerals Exploration – IP Survey in Mongolia ................................................................. 692 Minerals Exploration – Airborne Survey in Reid-Mahaffy Site, Canada ................................... 697 Hydrocarbon Exploration – Off-Shore EM Survey in North Sea.............................................. 701 17.5.1 The Acquisition Configuration and Survey Layout............................................ 702 17.5.2 3D Anisotropic Inversions of the Towed Streamer EM Data ................................ 704 17.6 Marine Magnetotellurics in the Gulf of Mexico ................................................................ 705 References and Recommended Reading to Chapter 17 .............................................................. 708

In the final chapter of the book, we present several case histories representing different applications of electromagnetic methods, from a regional scale to deposit scale. The first case history is related to a large-scale application of the magnetotelluric method in the framework of the EarthScope project. The second case history presents a crustal study based on the use of a powerful source of electromagnetic energy – a pulsed magneto-hydrodynamic (MHD) generator. The third and forth case histories illustrate the application of both land and airborne electromagnetic surveys for studying mineral deposits. The fifth case study provides an example of off-shore hydrocarbon exploration using a marine towed streamer EM system. Finally, we consider an example of a marine MT survey conducted in the Gulf of Mexico for mapping the salt structures.

17.1 TECTONIC STUDIES – EARTHSCOPE MT SURVEY IN THE NORTHWESTERN UNITED STATES The deep geological structure of the northwestern United States and southwestern Canada has been extensively studied by seismologists during recent years with the deployment of the National Science Foundation (NSF) EarthScope project’s USArray program, managed by the Incorporated Research Institutions for Seismology (IRIS), and regional seismic networks (e.g., Xue and Allen, 2007; Roth et al., 2008; Obrebski et al., 2010, 2011). One of the objectives of these studies was imaging the extent of the subducted Juan de Fuca plate in the mantle east of the Cascades beneath Oregon, and understanding the character of its interaction with the Yellowstone hotspot plume. It was shown in these publications that the subducting Juan de Fuca slab is expressed in the seismological models as a high-velocity anomaly which dips at approximately 46° to the east and extends down to a depth of about 400 km. For example, Obrebski et al. (2010, 2011) demonstrated that the subducting Juan de Fuca slab is clearly imaged by their P- and S-wave tomographic models, which also show a lowvelocity anomaly associated with the Yellowstone hot spot. Xue and Allen (2007) suggested that the Foundations of Geophysical Electromagnetic Theory and Methods. DOI: 10.1016/B978-0-44-463890-8.00021-9 Copyright © 2018 Elsevier B.V. All rights reserved.

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absence of the slab below 400 km today is due to the arrival of the Yellowstone plume head about 17 Ma, which destroyed the Juan de Fuca slab at depths greater than the thickness of the continental lithosphere. An important part of the EarthScope program is the EMScope project, which is the magnetotelluric (MT) component of the USArray program, managed by Oregon State University on behalf of IRIS. By the end of 2011, long-period MT data had been collected at 330 stations located in the following states: Oregon, Washington, Idaho, Wyoming, Montana, California, Nevada, Utah, and Colorado. Several research papers dedicated to interpretation of the EarthScope MT data collected over Washington, Oregon, Montana, and Idaho were published over several recent years (e.g., Patro and Egbert, 2008; Zhdanov et al., 2011b, 2012; Bedrosian and Feucht, 2013; ˇ Meqbel et al., 2013). Zhdanov et al. (2011b) and Cuma et al. (2017) presented one of the first 3D geoelectrical models of the upper mantle beneath Yellowstone based on the 3D inversion of EarthScope MT data from Montana, Idaho, and Wyoming. These images showed a highly conductive body associated with the tomographically imaged mantle plume-like layer of hot material emerging from the upper mantle toward the Yellowstone volcano. The conductive body identified in those images was west-dipping in a similar way to a P-wave low-velocity body (Smith et al., 2009). In the present chapter, as an example of a large-scale MT inversion, I present the results of the large-scale 3D MT inversion to EarthScope MT data collected over Oregon, Washington, Idaho, Wyoming, Montana, California, Nevada, Utah, and Colorado up to 2011. Considering the extremely large scale of the inversion of the entire EarthScope MT data collected in nine states of the northwestern United States, one has to use a moving sensitivity domain (MSD) approach outlined in Chapter 16 as applied to airborne EM data. In the framework of the MSD approach, for a given MT station one computes and stores the sensitivity matrix (Fréchet derivative) inside the inversion cells within a predetermined horizontal distance from this station only, i.e., within a sensitivity domain. Thus, Fréchet derivatives for an MT station can be computed and stored only for regions much smaller than the entire inversion domain, resulting in dramatic reduction of the computer memory requirements. The sensitivity domain size is determined based on the rate of sensitivity attenuation of the MT data. As the sensitivity attenuates faster for higher frequencies, one can vary the sensitivity domain size with frequency, which provides optimal memory and computation use while retaining maximum accuracy. Note that, the MSD approach is applied for the Fréchet derivative calculation only and not for the computations of the predicted field. By using all of the cells in the forward modeling computations, one can ensure an accurate result for the calculations of the predicted MT field components and impedances in the receivers. 3D inversion was applied to the EarthScope MT data collected at 260 stations shown by black stars in the physiographic map of the northwestern United States (Fig. 17.1). The station coverage extends from ∼123°W to ∼105°W and from ∼38°N to ∼49°N. The inversion was applied to all four components of the impedance tensor for 16 periods logarithmically spaced between 10 s and 10,000 s. The considered range of periods corresponds to a depth of investigation down to ∼500 km in a 100 Ohm-m host medium. The inversion domain was spanned in the X (geographic E-W), Y (geographic N-S), and Z (vertical downward) directions extending 1650 km, 1350 km, and 500 km, respectively. The sensitivity domain size for each station was determined as 450 km based on the rate of sensitivity attenuation of the MT data in a model of a 100 Ohm-m half space. The inversion domain contained 2,138,400 cells, and had an initial model of a 100 Ohm-m half space. The inversion was run until the L2 norm of the residuals between the observed and theoretically predicted MT data,

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FIGURE 17.1 Physiographic map of the northwestern United States indicating primary geologic-tectonic features [modified from Obrebski et al., 2011]. BM = Blue Mountains; BFZ = Blanco Fracture Zone; BR = Basin and Range; CR = Coast Range; IB = Idaho Batholith; HLP = High Lava Plains; MTJ = Mendocino Triple Junction; YNP = Yellowstone National Park. The locations of 260 MT stations used in the inversion are shown by black stars.

normalized by the L2 norm of the observed data, had decreased to about 10%. For the model presented in this chapter, the discretization cells had a horizontal size of 10 km by 10 km, and a vertical size starting from 1 km at the surface and logarithmically increasing with depth. The conductivity distribution as recovered by a 3D inversion of the EarthScope MT data reflects the regional lithological features of the northwestern United States. The inverse geoelectrical model correlates well with the seismic P- and S-velocity models obtained from inversion of body-wave travel times and surface-wave phase velocities (Obrebski et al., 2011). Fig. 17.1 shows major geologic-tectonic features of northwestern North America overlaid on topography and bathymetry (modified from Obrebski et al., 2010). They encompass the Cascadia subduction zone, including the descending Juan de Fuca and Gorda plates, which are the remnants of the convergent plate margin spanned over coastal western North America. According to modern geological and geophysical data, the Juan de Fuca plate is subducting beneath the North American plate. The estimated depth of the top of the subducting slab is shown with blue contours (labeled in km) in Fig. 17.1. The locations of all M > 4 earthquakes with depths >35 km since 1970 are shown as blue dots. Volcanoes are shown as orange triangles. The Snake River Plain traces the path of the North American plate over the Yellowstone hotspot, now centered

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FIGURE 17.2 Panel A: horizontal section of the geoelectrical model at a depth of 100 km, overlapped with a map of the major tectonic features of the northwestern United States. Panels B, C, and D: horizontal sections of the geoelectrical model at depths of 100 km, 200 km, and 300 km, respectively.

in Yellowstone National Park (YNP). The Columbia River Flood Basalt Province represents a massive outpouring of basalt from ∼16.6 to ∼15.0 Ma and is shown in pink (Camp and Ross, 2004). Fig. 17.2 presents horizontal sections of a geoelectrical model at depths of 100 km, 200 km, and 300 km (panels B, C, and D), respectively. Panel A of Fig. 17.2 shows a horizontal section at a depth of 100 km overlapped with a map of the major geologic-tectonic features of the Pacific Northwest of the United States, shown in Fig. 17.1. The subducting Juan de Fuca slab is clearly imaged in these horizontal sections. It is characterized by the zone of very high resistivity (≥1000 Ohm-m) shown by the dark blue vertical strip R1 in panels A, B, C, and D, which corresponds well to the known fact that the subducting oceanic lithosphere is very resistive (e.g., Wannamaker et al., 1989). We observe several conductive lineaments in the resistivity maps at 100 km depth. For example, conductive lineament C1 extends under the High Lava Plains to the NW toward the Blue Mountains (panels A and B). It can be associated with the northwestward propagating High Lava Plains volcanic lineament, and it

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FIGURE 17.3 Comparisons of the MT inversion result with the DNA09 seismic tomography model of Obrebski et al. (2011). The MT inversion result is presented as the vertical resistivity sections. Vp and Vs seismic velocities are shown as deviations from the mean value in percent. We present the vertical sections of the geoelectrical model and the P-wave and S-wave velocity models for the profiles, proceeding along the lines at latitude 40°N (panel A) and 42°N (panel B), respectively.

corresponds to the reduced velocity zone (RVZ) beneath the Newberry region, identified by Roth et al. (2008) from high-resolution, 3D P-wave tomography. Roth et al. (2008) explained the low-velocity anomaly beneath Newberry and the High Lava Plains by the presence of partially melted material due to the release of fluids from the downgoing slab. This partially melted material may also result in the decreased resistivity (∼5 Ohm-m), which is observed beneath the western side of the Blue Mountains. This hypothesis is supported by the geochemical characteristics of the Newberry basalts, which, according to Carlson et al. (2008) are strongly influenced by subducted slab-derived fluids. Another conductivity anomaly extends beneath the Columbia River basalts in south-central Washington (C2). This anomaly (∼5 Ohm-m) corresponds well to the reduced velocity zone identified by Roth et al. (2008) beneath the thick sections of the Columbia River basalts as related to the geothermal processes in the surrounding areas. An important feature of the inverse geoelectrical model is conductive lineament C3 extending beneath Yellowstone – Snake River Plain (YSRP) (Fig. 17.3, panels A and B). This conductive structure corresponds well to the reduced velocity anomaly within the Precambrian lithosphere identified by both Roth et al. (2008) and Obrebski et al. (2010, 2011), and is characterized by high temperatures and low density. We observe also conductivity anomaly C4 rising from the mantle at a depth of ∼100–200 km beneath Yellowstone, associated with the Yellowstone conductive plume-like layer identified by Zhdanov et al. (2011b) using a subset of the EarthScope MT survey of 28 MT stations located over the area surrounding Yellowstone National Park. The highly conductive body is associated with

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FIGURE 17.4 Comparisons of the MT inversion result with the DNA09 seismic tomography model of Obrebski et al. (2011) for the profile proceeding along the line at latitude 44°N (panel A), and for profile AA along the Snake River Plain (panel B).

the tomographically imaged mantle plume-like layer emerging from the upper mantle toward the Yellowstone volcano (e.g., Schutt and Dueker, 2008; Schutt et al., 2008; Schmandt and Humphreys, 2010; Yuan and Dueker, 2005; Waite et al., 2005; Smith et al., 2009). Figs. 17.3 and 17.4 show comparisons of the MT inversion result with the DNA09 seismic tomography model of Obrebski et al. (2011). The MT inversion result is presented as the vertical resistivity sections along the lines at altitude 400 N, and 420 N, respectively. Vp and Vs seismic velocities are shown as deviations from the mean value in percent. The subducting Juan de Fuca slab is clearly imaged by the geoelectrical model as a high-resistivity anomaly (R1) dipping east under 450. It is manifested in the P- and S-wave tomographic models of Obrebski et al. (2010, 2011) as the highvelocity anomaly which dips east under a similar ∼46°. We also can see the conductive zone of partially melted material directly above the subducting slab, which can be explained by the release of fluids from the down-going slab. Vertical resistivity sections of the geoelectrical model of the northwestern United States show large zones of moderate-to-high conductivity (∼5–10 Ohm-m) below 100–200 km in the upper mantle, which represent the electrical properties of the conductive electrical asthenosphere (C5). Fig. 17.4, panel B, presents vertical sections of the geoelectrical model and P-wave and S-wave velocity models for the profile AA , proceeding along the Snake River Plain (see Fig. 17.1) over the traces of the path of the North American plate over the Yellowstone hotspot. The Yellowstone hot conductive layer is clearly imaged in the geoelectrical model as a low-resistivity (∼1–5 Ohm-m) anomaly

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(C4). It is also manifested in the P- and S-wave tomographic models of Obrebski et al. (2010, 2011) as the low velocity zone. The conductivity of the plume-like layer is higher in the relatively shallow part (∼150 km) and decreases with the depth, diffusing below 300 km. This observation correlates well with the seismic models of Obrebski et al. (2010, 2011), which are characterized by the lower velocity anomaly at the shallow, elongated part of the plume-like layer extending to depths of about ∼300 km. Both of these observations are consistent with the presence of partial melt, which decreases the seismic velocity and increases the electric conductivity. As was discussed in Zhdanov et al. (2011b), the low resistivity of the conductive structure (on an order of 1 to 5 Ohm-m) is comparable to the resistivity of silicate melts determined from laboratory experiments (Pommier et al., 2008), and it is explained by a combination of high temperature partial melt, and the presence of highly saline fluids present in magmatic processes. The low velocities and high conductivity layer initially dip slightly toward the northwest in the upper mantle, consistent with the northwest dip of the mantle plume-like layer seen in published images beneath Yellowstone (e.g., Smith et al., 2009; Zhdanov et al., 2011b).

17.2 CRUSTAL STUDIES – THE KHIBINI EXPERIMENT In the development of modern EM methods capable of exploring the Earth to depths of many kilometers, the limit to the depths that can be reached is always imposed by the signal strength. For example, to double the depth that can be reached, one has to increase the strength of the source by about an order of magnitude. The source strength for an EM field is measured in terms of the source moment. Therefore an increase in source moment by an order of magnitude requires an increase in source power by two orders of magnitude. This can be achieved in several ways. The most direct approach is through the use of a transmitter of greater power. Another approach to increasing the strength of a signal is by repetitious transmissions of low power, with synchronous stacking of the signals at a single receiver site. With long-term robust stacking, the ratio of signal level to noise grows roughly as the square root of the number of transmissions. The energy expended in stacking increases in direct proportion to the number of transmissions. Both of these approaches to increasing effective source moment have very real practical limits. Increasing the power available to energize a source requires the use of a primary energy source whose mass grows more or less directly with power capability, if only conventional generators are considered. So the maximum practical generator size and the longest stacking time that can be afforded should be taken into account when designing EM surveys. To achieve significantly greater depth of sounding requires a departure from the use of conventional EM sources. An idea for the application of pulsed magneto-hydrodynamic (MHD) generators in EM surveying was originally introduced in the 1970s by Russian physicist Evgeny Pavlovich Velikhov (Velikhov et al., 1975). An MHD generator extracts energy from a stream of heated, ionized gas as it flows through a magnetic field. The primary energy source is a charge of solid fuel, not unlike rocket fuel, but with chemical additives, such as a potassium salt, to make the temperature of the burning plume of fuel hot enough to ionize to a significant degree. The ionized gas, or plasma, is directed through an electromagnet, which causes the cations and anions in the plasma to deflect in opposite directions. These ions then flow into a channel, where they are collected on plates connected to an external ground circuit. Initially, when the generator is first fired, the magnetic field is powered with batteries which

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cause current to flow in an excitation loop. Once current flow is established in the external circuit, a portion of the produced current is diverted to excite the magnetic field. One of the first practical applications of an MHD generator for EM soundings was performed in the framework of the Khibini experiment, conducted in the 1980s in the USSR. The Khibini experiment was designed to test the concept of using single, immensely strong impulses of an MHD generator (Velikhov, 1989). This powerful MHD generator was used to energize a single conductor, 11 km in length, connecting grounding structures in the Barents Sea on either side of the Sredniy and Ryabachiy Peninsulas. The maximum current provided to the cable was 22,000 A, in pulses with a duration of 5 to 10 seconds. The site for the Khibini source was selected so that the current from the two grounding structures would travel around the Sredniy and Ryabachiy peninsulas, forming an equivalent loop in the horizontal plane. Observations belong to two groups, one comprising the stations to the south on the Precambrian Shield of the Kola Peninsula (Fig. 17.5, bottom panel), and the other comprising stations to the north, off the shore of the Kola Peninsula, over the Barents Basin (Fig. 17.5, top panel). The geological formations beneath the Barents Sea are formed by young sedimentary rocks with significant potential for oil or gas production. For example, the massive Shtokman gas field is located within this area. Evaluation of the deep potential of the Pechenga deposit was another important problem that was solved using EM surveying with MHD-generated pulses (Velikhov et al., 1987). The data obtained as part of the Khibini experiment were used for a variety of purposes: to study the electrical conductivity profile in the earth to depths of several hundred kilometers, to study the electrical structure of major ore deposits in the Kola Peninsula, and to determine the character of the sedimentary basin beneath the Barents Sea. A profile of MHD soundings was established across the Pechenga mineral deposit located on the Kola Peninsula, and a major source of nickel ore. The Proterozoic Pechenga complex consists of a laminar sequence of alternating metasedimentary and metavolcanic rock (Kozlovskiy, 1987). The total thickness of this sequence may be as great as 8–9 kilometers. The ore body lies in a simple graben-like structure on the surface of the Archean basement. The underlying Archean complex is composed principally of gneisses which have been repeatedly metamorphosed and which have undergone regional granitization of varying degree. The extent of the ore in the Pechenga deposit is not yet fully known. Levels which have been developed to date extend to depths of 1500 to 2000 meters, but it is believed that substantial reserves remain undiscovered at depths between 3 and 5 kilometers. Evaluation of the deep potential of the Pechenga deposit was considered to be an important problem that might be solved using MHD-generated pulses. Inversion of the data collected in the framework of the Khibini experiment has indicated that in northern Finland, there is a very rapid decrease in resistivity from values of the order of 500 Ohmmeters to values of the order of 10 Ohm-meters at depths ranging from 140 to 170 kilometers. On the other hand, the inversions of sounding curves from the Kola Peninsula and Karelia indicated a gradational decrease in resistivity starting at a depth of about 150 kilometers. In these cases, the resistivity does not decrease to a resistivity of a few tens of Ohm-meters until depths of 300 kilometers or more are reached. The results of the Khibini experiment can be summarized as follows (Velikhov and Panchenko, 2010): – ten large geoelectrical blocks and zones in the upper section of the earth’s crust up to depth of 10–15 km with dimensions about 50 km × 50 km have been detected; – the resistivity of the blocks varies from ∼10 Ohm-m to ∼100 Ohm-m;

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FIGURE 17.5 Survey configuration of the Khibini experiment. The red line in the top panel schematically shows the current flow off the shore of the Kola Peninsula, over the Barents Sea. The bottom panel presents the locations of the observation stations in the Kola Peninsula shown by circles. The black lines show the profiles of detailed EM soundings: (I–I) – Pechenga ore-bearing structure, (II–II) – Imandra-Varzug ore-bearing area, (III) – Barents Sea shelf, (IV–IV) – profile of the deep sounding of the Baltic Shield.

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– the blocks with high resistivity usually correspond to the outcrops of the most ancient granitoid rocks; – the blocks with low resistivity, as a rule, are connected to the outcrops of the younger rocks, and they are considered to be prospective zones for exploration for ore deposits and other mineral resources. The Khibini experiment was one of the first large-scale experiments of deep EM sounding using high-power pulses. It provided geophysicists with a unique opportunity to test new technologies for studying a deep earth interior using a controlled-source EM field. However, the further development of an EM surveying system with a very powerful MHD generator was limited by the high cost of this exploration tool. With the progress in MHD technology and the simplification and cheapening of the operation, this method could become a power tool in regional and crustal tectonic study associated with the exploration of the Earth’s resources.

17.3 MINERALS EXPLORATION – IP SURVEY IN MONGOLIA The induced polarization (IP) geophysical method has been widely used for mineral exploration. This method makes it possible to estimate not only the resistivity distribution but also the chargeability distribution of the underground remotely using the surface electromagnetic (EM) data. However, the

FIGURE 17.6 A QEMSCan image of rock sample A from the Au-Cu deposit, with a phase analysis shown on the right. The feldspar and quartz are designated by the dark green and light pink colors, respectively, while the dolomite is shown by blue, the chalcopyrite by orange, and the pyrite by yellow in this image.

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FIGURE 17.7 Real (top panel) and imaginary (bottom panel) parts of the observed complex resistivity spectrum (black dots) and the data predicted based on the GEMTIP model (black lines) for the rock sample A. The predicted data were obtained using three-phase GEMTIP model.

IP effect depends not only on the resistivity and chargeability. Several other geoelectrical parameters affect the IP data as well. A comprehensive analysis of IP phenomena is usually based on models with frequency dependent complex conductivity distribution. One of the most popular models is the ColeCole relaxation model (Cole and Cole, 1941). This model was introduced for studying the IP effect in the pioneering papers of Pelton (1977) and Pelton et al. (1978). It was demonstrated in Chapter 12 that the generalized effective-medium theory of induced polarization (GEMTIP), based on a rigorous physical-mathematical description of heterogeneous conductive media, provides a more accurate representation of the IP phenomenon than the Cole-Cole model. The GEMTIP model of multiphase conductive media provides a quantitative tool for evaluation of the type of mineralization, and the volume content of different minerals using electrical and/or electromagnetic data. The time-domain IP geophysical survey with pole-dipole and gradient electrode arrays, were carried out over the Cu-Au deposit in Mongolia in an area located about 1800 km west from Ulan Bator, and about 150 km from the Bayan-Ulugii province center. The copper-gold ore is hosted in the hydrothermal alteration zone. The mineralization is a low-sulfide type. The distribution of the mineralization is uneven and it was determined that the mineralization is generally distributed in or in the vicinity of the quartz-carbonate gangue located inside of the hydrothermal alteration zone. Mineralization is

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FIGURE 17.8 A 3D view of the 3D resistivity model recovered from 3D inversion of pole-dipole IP data.

associated with chalcopyrite related to early quartz veins. The main exploration problem in this case is the ability to differentiate between normally barren pyrite-bearing alteration phases and mineralized chalcopyrite phases. These geological systems generally always have pyrite but not all are mineralized with Cu bearing sulfides. Discrimination between pyrite and chalcopyrite could be considered as an important application of the IP survey. The main objective of this survey was to determine the alteration and mineralization zones of the known copper deposit. The mineralogical analyses of mineral and host rock samples from the survey area were performed using the quantitative evaluation of minerals by the scanning electron microscopy (QEMSCan) system, developed from the research pioneered by the CSIRO in Australia. QEMSCan combines features found in other analytical instruments such as a scanning electron microscope (SEM) or electron probe micro analyzer (EPMA) into a next generation solution designed for automated analysis of minerals, rocks and materials. QEMSCan uses electron beam technology combined with high resolution BSE (back scattered electron) and SE (secondary electron) imaging, and state-of-the-art energy dispersive spectrometers (EDS) to analyze minerals. QEMSCan provides detailed particle mineralogical analysis including quantification of mineral proportions, average grain size for selected minerals, average grain density, estimated minerals frac-

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FIGURE 17.9 A 3D view of the 3D chargeability model recovered from 3D inversion of pole-dipole IP data.

tion volumes, etc. The final QEMSCan images were used for determination of the fraction volume of different minerals. As an example, Fig. 17.6 presents the results of the QEMSCan analysis for a rock sample A. A QEMSCan image of rock sample A (Fig. 17.6) contains quartz (light pink, veins) and feldspar (light green, matrix) with 2.64% of pyrite (yellow) and 0.15% of chalcopyrite (orange). The sulfides are located inside of quartz veins in this sample. The electrical properties of the same samples from the Cu-Au deposit in Mongolia were determined using the laboratory complex resistivity (CR) measurements. Fig. 17.7 shows the real and imaginary parts of the complex resistivity spectra measured for the same sample A analyzed above. We can see that the maximum IP response in the imaginary part of the complex resistivity curves (the minimum of imaginary part) corresponds to a frequency of around 1 Hz in this case. The observed CR data were inverted into the IP parameters using a three-phase GEMTIP model with elliptical inclusions (see section 12.3.6). In this case, it was assumed, based on the results of the QEMSCan analysis, that one phase was represented by pyrite, another phase by chalcopyrite, and the third phase was formed by other nonpolarizable minerals. The predicted data obtained using the three-phase GEMTIP model are shown by the black lines in Fig. 17.7.

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FIGURE 17.10 A 3D view of the 3D time constant model recovered from 3D inversion of pole-dipole IP data.

As a result, one can establish relationships between the mineral composition of the rocks, determined using QEMSCan analysis, and the parameters of the GEMTIP model defined from lab measurements of the electrical properties of the rocks. These relationships open the possibility for remote estimation of types of mineralization and for mineral discrimination using spectral IP data. The time-domain IP data, collected by the IP survey, were inverted for the GEMTIP model parameters, DC resistivity, chargeability, time constant, and relaxation parameter, using the inversion method discussed in section 12.4. Figs. 17.8 through 17.11 show the 3D distributions of resistivity, chargeability, time constant, and relaxation parameter, recovered from 3D inversion of pole-dipole IP data. It was possible to locate the target mineralization zones by using geoelectrical models recovered from 3D inversion of the IP data, petrophysical and mineralogical analyses of the rock samples, and assay data analysis of the drill cores. The result of this comprehensive interpretation is shown in Fig. 17.12, which presents a 3D view of the interpreted target mineralized zones. In that figures, the color of the body corresponds to the chargeability value recovered from the 3D inversion of the IP data (hot color – high chargeability; cold color – low chargeability). The drilling results confirmed a good correlation between the interpreted bodies and known mineralization. This opens a possibility to

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FIGURE 17.11 A 3D view of the 3D relaxation parameter model recovered from 3D inversion of pole-dipole IP data.

estimate the target mineralized zones by using a rigorous 3D inversion of the IP data interpreted with petrophysical and mineralogical analyses of rock samples, and assay data analysis.

17.4 MINERALS EXPLORATION – AIRBORNE SURVEY IN REID-MAHAFFY SITE, CANADA The Reid-Mahaffy site is located in the Abitibi Subprovince, immediately east of the Mattagami River Fault. The area is underlain by Archean (about 2.7 b.a.) mafic to intermediate metavolcanic rocks in the south, and felsic to intermediate metavolcanic rocks in the north, with a roughly EW-striking stratigraphy (Fig. 17.13). Narrow horizons of chemical metasedimentary rocks and felsic metavolcanic rocks have been mapped, as well as a mafic-to-ultramafic intrusive suite to the southeast. NNW-striking Proterozoic diabase dikes are evident from the aeromagnetic data. Copper and lead-zinc vein/replacement and stratabound volcanogenic massive sulfide (VMS) mineralization occur in the immediate vicinity. The world-class Kidd Creek VMS deposit occurs to the southeast of the test site. Drill holes within the

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FIGURE 17.12 A 3D view of the interpreted target mineralized zones.

test site were targeting conductive targets, and encountered massive sulfides and graphite with minor copper and zinc mineralization. Many different airborne systems have been tested in this area, including the DIGHEM frequency domain system, which is the focus of this paper. The DIGHEM system was configured with five operating frequencies: 868, 7025, and 56,374 Hz horizontal coplanar, and 1068 and 4820 Hz vertical coaxial. The transmitter-receiver separation was 6.3 m for the highest frequency and 8.0 m for the remainder. The survey was flown with a nominal bird height of approximately 32 m. The AEM data from the Reid-Mahaffy test site have previously been interpreted using a variety of 1D AEM methods (e.g., Sattel, 2005; Vallée and Smith, 2007, 2009), as well as 3-D inversion from Cox et al. (2010, 2012). I present hear the inversion result for a 3-D conductivity model with elements that were 20 m in the in-line direction and 25 m in the cross-line direction, and varied from 5 m to 20 m in the vertical direction. The model had a total depth of 160 m. The sensitivity domain of the DIGHEM system was set at 280 m. The 3-D inversion for the DIGHEM data converged to a final misfit of 5% from an initial misfit of 70%. Fig. 17.14 is an example of the conductivity model recovered from the 3-D inversion. It clearly shows conductive overburden between 20 Ohm-m and 50 Ohm-m, and three vertical conductors in the correct location as determined by drill holes.

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FIGURE 17.13 Geologic map of the Reid-Mahaffy survey area.

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FIGURE 17.14 Perspective view of the resistivity model recovered from 3-D FE-IE-based inversion of the Reid-Mahaffy test site, Ontario. For clarity, the conductive overburden has been removed from the volume rendering in this image, but is clearly seen in the opaque slices.

FIGURE 17.15 The location of the Mariner field in the North Sea.

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FIGURE 17.16 A map of the Mariner area showing the acquired lines and shot points.

17.5 HYDROCARBON EXPLORATION – OFF-SHORE EM SURVEY IN NORTH SEA As an example of application of the EM methods for off-shore hydrocarbon exploration, let us consider a case study of analysis of the towed streamer EM data acquired over the Mariner heavy oil field located in the UK North Sea (Zhdanov et al., 2015). The Mariner field is located on the East Shetland Platform of the UK North Sea approximately 150 km east of the Shetland Isles (Fig. 17.15). The Mariner oil field development entails investments of more than USD 7 billion and is the largest new offshore development in the UK in more than a decade. It is expected to start production in 2017. The field is estimated to produce for 30 years, with average production of around 55,000 barrels of oil per day over the plateau period from 2017 to 2020. The Mariner field consists of two shallow reservoirs, the Maureen Formation and the Heimdal Sandstones of the Lista Formation, with nearly 2 billion barrels of oil in place and expected reserves of more than 250 million barrels of oil. Both formations yield heavy oil of around 12 to 14 API. Due to the low well flow rates and early water break-through there is a need for many wells and a process designed to handle large liquid rates and oil-water emulsions.

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FIGURE 17.17 Horizontal sections of the 3D resistivity distributions at a depth of 1425 m: (A) vertical resistivity, (B) horizontal resistivity, recovered from anisotropic 3D inversion.

All production wells will have stand-alone sand screens and electric submersible pumps (ESPs) for lifting.

17.5.1 THE ACQUISITION CONFIGURATION AND SURVEY LAYOUT The main features of the towed streamer EM configuration for the Mariner survey (Mattsson et al., 2012; Zhdanov et al., 2015) are shown in Fig. 15.23. The bipole electric current source is 800 m long with a towing depth of 10 m. The source runs at 1500 A, and the frequencies range from 0.2 to 1.2 Hz with a step of 0.2 Hz. The survey consisted of 10 lines separated by 500 m, as shown in Fig. 17.16. The length of each line was about 15 km. Each line recorded 60 shots of 120 s lengths. In order to construct an appropriate 3D geoelectrical model which is used as the starting model in the anisotropic 3D inversion, one can apply anisotropic 1D inversion for each survey line. For all 1D inversions, the bathymetry in the survey area was taken into account, and the response data at five frequencies from 0.2 to 1.0 Hz with 18 offsets ranging approximately from 1750 to 7450 m were used. The final starting model was constructed using a 3D model from the results of 1D inversions, geometrically constrained by seismic and well-log information (Zhdanov et al., 2015).

17.5 HYDROCARBON EXPLORATION – OFF-SHORE EM SURVEY

FIGURE 17.18 A 3D view of the 3D vertical resistivity distribution recovered from anisotropic 3D inversion.

FIGURE 17.19 A 3D view of the 3D horizontal resistivity distribution recovered from anisotropic 3D inversion.

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FIGURE 17.20 Location of Gemini Prospect in the northern Gulf of Mexico.

17.5.2 3D ANISOTROPIC INVERSIONS OF THE TOWED STREAMER EM DATA In the anisotropic 3D inversion of the data collected from all the survey lines, the inversion domain was selected to cover all sensitive parts of the subsurface. The dimensions of the inversion domain were selected as follows: from −12,000 m to 16,000 m in the x direction; from −3600 m to 3600 m in the y direction; from 90 m to 3000 m in the z direction (positive downward). This rectangular region was discretized into cells of 50 m × 50 m × 25 m. The selected data for the inversion consisted of 323 shots with 18 offsets (approximately from 1750 m to 7450 m) and five frequencies (0.2, 0.4, 0.6, 0.8, and 1.0 Hz). The RCG algorithm of inversion was terminated when a resulting misfit of 5.4% was reached. Fig. 17.17 presents examples of the horizontal sections of the 3D resistivity models at a depth of 1425 m recovered from the anisotropic 3D inversion. Figs. 17.18 and 17.19 show 3D perspective views of the 3D resistivity models recovered from the anisotropic 3D inversion of the towed streamer EM data for vertical and horizontal resistivities, respectively. It can be seen that a resistive and anisotropic anomaly is showing up on top of a resistive chalk/basement underburden. This anomaly coincides well with the horizontal extent of the Heimdal and Maureen reservoirs even though this information was not exactly utilized in the anisotropic 3D inversion. Also, the recovered anisotropic feature in the reservoir volume agrees well with the known geoelectrical characteristics of the Maureen and Heimdal reservoirs.

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FIGURE 17.21 Location of the MT profiles with the observation sites in Gemini Prospect. (After Key, 2003.)

17.6 MARINE MAGNETOTELLURICS IN THE GULF OF MEXICO There were several marine MT surveys conducted during the last decade in different areas of the World Ocean. We will discuss here, as an example, an application of the marine MT method for mapping the salt structures in the Gulf of Mexico. Salt bodies are usually characterized by a higher seismic wave velocity and higher resistivity than the surrounding sea-bottom sediments. They represent a very difficult target for marine seismic exploration, but can be clearly identified by marine EM methods. In this section we discuss the results for the marine MT surveys in the Gemini Prospect, which lies about 200 km southeast of New Orleans in about 1 km deep water in the northern Gulf of Mexico, which is shown in Fig. 17.20. The reflection imaging technique, widely available and ever popular in exploration, can provide detailed images of the top and base of a salt surface, sedimentary layer, and basement formations. However, seismic imaging may not always provide sufficient details to interpret salt and nearby sedimentary structures. Common problems associated with salt include multiple reflection and mode conversion, the

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FIGURE 17.22 Plots of the observed (left-hand panels) and predicted (right-hand panels) apparent resistivity and phase for the MT data collected at the MT sites in the Gemini Prospect area.

loss of reflected energy from steeply dipping salt surfaces, and lack of coherent features beneath salt structures. The salt in the Gulf of Mexico has a high acoustic contrast with surrounding sediments, which makes seismic sections difficult to interpret. It is generally well known that rocks with high seismic velocity and impedance contrast are also higher in electrical resistance than surrounding sediments. The high contrast in electrical conductivity between the salt and the surrounding sediments makes Gemini Prospect an attractive target for MMT method. The sea-bottom MT surveys were conducted by the Scripps Institution of Oceanography in 1997, 1998, 2001, and 2003, at a total of 42 MT sites.

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FIGURE 17.23 A vertical cross section of 3-D focusing inversion results provided over line A. The observational profile is oriented from southwest (left) to northeast (right). The MT site locations are shown as black diamonds. The resistivity distribution in the inverse model is shown on a linear scale. The inverse geoelectrical model is overlapped with the depth-migrated seismic reflections from a 3-D seismic survey.

The Gemini salt body lies 1.5 km beneath the seafloor in 1 km deep water and has a high electrical resistivity compared with the surrounding sediments, making it a suitable target for electrical methods. The subsalt gas deposit at Gemini is located at a depth of about 4 km on the southeastern edge of the Gemini structure. Fig. 17.21 shows the location of the MT sites. Constable and Key (Key, 2003) conducted a detailed analysis of the Gemini MT data, using 2-D Occam’s inversion code (Constable et al., 1987; de Groot Hedlin and Constable, 1990). The results obtained by 2-D inversion of the MT data were in a good agreement with the seismic data (Key, 2003; Key et al., 2006). We consider here the results of a rigorous 3-D MT inversion of the same data using a fine discretization grid following the paper by Zhdanov et al. (2011c). We analyzed the MT data from all 42 sites simultaneously. Inversion is conducted by the re-weighted regularized conjugate gradient method, RRCG (Chapter 8). The discretization is 128 × 120 × 64 = 983,040 cells. The iterative process is terminated when the relative norm of the difference between the observed and predicted data, computed over all MT sites, reaches the noise level of 7%. Fig. 17.22 presents plots of the observed and predicted apparent resistivity and phase for the MT data collected in the observational sites shown in Fig. 17.21. We observe a good fit between the observed and predicted data in this figure. Fig. 17.23 presents, as an example, the vertical cross section of a 3-D resistivity model obtained by focusing inversion along the observational line A, shown in Fig. 17.21. The depth-migrated seismic reflections from a 3-D seismic survey are shown by the black line, for comparison. We can see the top part of the salt dome very clearly in these figures as a thick resistive

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FIGURE 17.24 3D image of the inversion result for the Gemini Prospect MT data in the presence of the sea-bottom bathymetry.

body. Fig. 17.24 presents a 3D view of the geoelectrical inverse model and the bathymetry in the area of the survey. The inversion results reveal a resistive salt structure which is confirmed by a comparison with the seismic data. These inversion results demonstrate that we can map resistive geoelectrical structures like salt domes with reasonable accuracy using 3D inversion of marine MT data.

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