Cross-Reference to Related Applications

[0001] This application claims the benefit of U.S. Provisional Application No. 61/621,844, entitled "APPARATUS AND METHOD FOR HEAP LEACHING DYNAMIC

MONITORING," filed April 9, 2012, the entire disclosure of which is hereby incorporated herein by reference.

Background of the Disclosure

[0002] Once a leachant fluid agent is injected into a man-made heap, there are indirect methods for determining how effectively the agent is spatially distributed. This distribution is measured to determine a uniform distribution that may maximize the Net Present Value (NPV) of the heap asset, as a by-passed pay-zone may decrease NPV and producible reserves.

Examples of the methods for determining the agent distribution may rely on long-range electromagnetic (EM) measurements utilizing EM induction or resistivity measurements. An EM survey may, for example, be utilized to identify zones of high or low resistivity, where the low resistivity may be associated with a high saturation of leachant fluid. However, this interpretation may be complicated by the fact that one cannot separate this signal from the similar signal coming from free ions in solution, salinity, temperature, and from the rock mineralogy itself. Seismic survey methods may utilize a three-dimensional (3D) density probe that may be sensitive to the local velocity of sound. However, while related, it may not represent a unique function of the local density.

Brief Description of the Drawings

[0003] The present disclosure is best understood from the following detailed description when read with the accompanying figures. It is emphasized that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion.

[0004] Fig. 1 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0005] Fig. 2 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure. [0006] Fig. 3 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0007] Fig. 4 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0008] Fig. 5 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0009] Fig. 6 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0010] Fig. 7 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0011] Fig. 8 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0012] Fig. 9 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0013] Fig. 10 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0014] Fig. 11 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0015] Fig. 12 is a schematic view of at least a portion of an apparatus according to one or more aspects of the present disclosure.

[0016] FIG. 13 is a flow-chart diagram of at least a portion of a method according to one or more aspects of the present disclosure.

Detailed Description

[0017] It is to be understood that the following disclosure provides many different embodiments or examples for implementing various aspects within the present scope. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. In addition, the present disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. [0018] One or more aspects of the present disclosure relate to the field of subsurface monitoring. Example extraction processes in the mining industry include heap leaching, wherein excavated primary ore is agglomerated and stacked on a surface heap and then saturated with a leachant agent to extract valuable minerals (such as copper and gold, among others).

[0019] The present disclosure introduces one or more aspects of methods of monitoring the distribution of leachant solutions, steam, fluids, and/or other production-assisting agent fluids, such as may be utilized to optimize the NPV of the asset. In the scenarios described above, passage of the agent fluid results in a net change of the local heap density. This may be determined utilizing a density tomography technique based on the measurement of the natural cosmic ray flux. For a given incoming flux at the surface, the muon rate under a heap of material is dependent on the material density integrated along the particle (muon) trajectory. Measuring the underground muon flux along different directions may be utilized to generate a density distribution or "map" of the heap. For example, a 3D density distribution may be generated utilizing a plurality of muon detectors at varying view angles with respect to the object or volume under investigation. Each of the muon detectors may be operable to detect the passage of single -particle muon events and determine their direction (tracking). Such muon tracking may be accomplished utilizing scintillation detection techniques, gas ionization detection techniques, transition radiation detection techniques, techniques utilizing Cerenkov detectors, and others within the scope of the present disclosure.

[0020] Developing the 3D density distribution may comprise normalizing the observed event rate along any given direction relative to the incoming muon rate. The incoming muon rate may be dependent on location (such as altitude, latitude, longitude, nearby geographical features, and/or other characteristics), atmospheric conditions (such as the density of the overlying air column, among other conditions), and/or space-weather conditions (such as those due to the effects of solar cycles, solar winds, and/or the Earth's magnetic field), among other factors. Normalization may be relative to the incoming muon flux measured by one or more reference detectors. Normalization may alternatively or additionally be relative to the muon flux measured along a fixed reference direction. For example, when normalization is relative to the muon flux measured along a reference direction, a density variation map may be generated across the heap relative to a specific area of the heap. The one or more reference detectors may also or alternatively comprise one or more detectors operable to measure the muon flux in a direction along which there are no density changes. For example, in heap leach dynamic monitoring (HLDM), one or more reference detectors may be positioned at the edges or outside of the heap, such as to monitor the flux primarily outside the heap. Similarly, a cosmic ray detector placed close to the edge of the heap may be able to simultaneously monitor the muon flux outside the heap and muon flux through the heap.

[0021] The positions and/or characteristics of the one or more reference and/or monitor detectors may be optimized by one or more survey optimization and/or design techniques. For example, this may comprise one or more forward-model simulation studies referenced against one or more models of the agent fluid distribution in the heap and/or other models. Such simulation studies may also be utilized to determine optimized shapes and/or segmentation of the one or more detectors. Segmentation, such as by means of layered detector planes or surfaces in a crossing pattern (such as X-Y patterns, chevron patterns, helicoidal patterns, and/or others), may be utilized to determine the track-resolving capabilities of the one or more detectors.

Greater segmentation may increase the accuracy of track reconstruction, which may result in a more refined density distribution. However, segmentation may also increase costs, such as may be due to increased detector and/or electronics channel count.

[0022] The muon detectors may be arranged in planar and/or other arrays that are positioned in tunnels, caves, pits, and/or at the foot of a heap, and which may be subsequently covered by one or more stacked ore layers. To optimize geometrical coverage over large areas in a cost- effective manner, a distributed sensor placement may utilize a string of detectors along a suitable pattern, such as may include one or more two-dimensional (2D) patterns and/or lattices.

[0023] The spectrum of energetic cosmic rays on the earth surface is dominated by muons that are formed at the edge of the atmosphere by incoming primary cosmic radiation. The muon flux on Earth exhibits a peak at energies of around a few GeV (1-10, depending on angle) followed by a long tail up to much higher energies (»10 TeV), wherein the flux drops rapidly with energy (~1/E ^3'7 ). Even at energies as high as 1 TeV, the surface flux is of about 10,000 events per square meter per day.

[0024] The penetrating muons are ultimately slowed down and stopped due to energy loss. Muon energy loss in heap leach fields follows the well-known mechanisms common to all charged particles, namely, ionization and radiative losses predicted by the Bethe-Block and Bremsstrahlung formulas, respectively. This implies that for a given layer within the heap leach field, the minimum entrant energy for the muon to penetrate the layer can be determined based on the density and thickness of the layer. Conversely, if the distribution of cosmic muons entering a region of unknown thickness or density within the heap leach field is known, then a measurement of the muon flux at depth directly yields the integral of density x length along the muon trajectory through the region.

[0025] Moreover, the incoming cosmic ray flux at the surface of the heap leach field can be measured and/or obtained through simulations such that, by simple geometry, the path lengths of cosmic ray events measured with muon track-sensitive detectors within the heap leach field can be determined. Consequently, the average density at multiple locations within the heap leach field may be determined.

[0026] FIG. 1 is a schematic view of at least a portion of a system 100 deployed in a heap leach field 110 according to one or more aspects of the present disclosure. Cosmic ray muon detectors 120 are deployed at various depths and positions within the heap leach field 110.

Muon tracks 130 and 131 are shown passing from the surface 112 of the heap leach field 110 through several of the detectors 120. The detectors 120 may be permanently, semi-permanently, or temporarily deployed within the heap leach field 110 to generate a density distribution of the field according to one or more aspects of the present disclosure.

[0027] The cosmic ray muon detectors 120 are each operable to measure the muon flux traversing the heap leach field 110 below the surface 112. The relative count rate at each of the cosmic ray muon detectors 120 is dependent upon the density and/or other properties of the heap leach field 110. One or more of the cosmic ray detectors 120 may be or comprise position- sensitive segmented detectors operable for the reconstruction of the muon tracks. For example, as shown in FIG. 1, muon track 130 is detected by two of the detectors 120, while muon track 131 is detected by three of the detectors 120. Utilizing standard techniques, data from the intersected detectors 120 may be inverted to reconstruct a portion of a 3D density distribution of the heap leach field 110. By selecting the proper relative detector alignment, and by measuring events simultaneously crossing multiple detectors, muon events that traverse the heap leach region 110 may be tagged. Alternatively, or additionally, the detectors 120 may be segmented, such that each detector 120 may be individually utilized to determine muon track 130. Examples of such segmented detectors 120 are described below.

[0028] The particular number and relative orientation of the cosmic ray muon detectors 120 may vary from the example illustrated in FIG. 1. For example, the detectors 120 may be positioned such that different detectors may measure intersecting muon tracks. Consequently, at least a portion of the heap leach field 110 may be sub-divided into voxels, and a 3D reconstruction of the subsurface density distribution may be obtained with standard inversion techniques.

[0029] The system 100 may also comprise an additional cosmic ray muon detector 140 on or close to the surface 112. The additional detector 140 may act as an independent monitor with which to normalize the flux measured by the submerged detectors 120 to the total incoming muon flux. For example, the detectors 120 may be able to determine the muon tracks while the surface detector 140 may act as an independent monitor of the local terrestrial muon flux. That is, the subsurface count may be normalized to the monitor rate, and events that traversed the heap leach field 110 may be selected in the analysis of the recorded tracks.

[0030] The system 100 may also comprise a processor 150 operable to generate the density distribution of a substantial portion of the heap leach field 110 based on the optical signals generated by the plurality of cosmic ray muon detectors 120. The processor 150 may receive the signals generated by the detectors 120 and/or 140 by a plurality of communications links 160 each extending between the processor 150 and a corresponding one of the detectors 120/140. The communications links 160 may comprise one or more of an electrical cable, a radio- frequency and/or other wireless channel, and/or combinations thereof, among others within the scope of the present disclosure. The communications links 160 may link each detector 120 to the processor 150 directly, or via another one or more of the detectors 120 in a daisy-chain or other arrangement.

[0031] FIG. 2 is a schematic view of an example implementation of the system 100 deployed in the heap leach field 110 according to one or more aspects of the present disclosure. As shown in FIG. 2, each detector 120 may be utilized to monitor a section 114 of the heap leach field 110. Each section 114 may have a diameter ranging between about 100 m and about 150 m, although other dimensions are also within the scope of the present disclosure. Each detector 120 may have a substantially square footprint having lateral dimensions of about 1 m, although other dimensions are also within the scope of the present disclosure. The detectors 120 may be permanently, semi-permanently, or temporarily deployed within the heap leach field 110, and may be utilized in the generation of a density distribution of the field according to one or more aspects of the present disclosure.

[0032] FIG. 3 is a schematic view of another example implementation of the system 100 deployed in the heap leach field 110 according to one or more aspects of the present disclosure. As shown in FIG. 3, each detector 120 may be utilized to monitor a section 116 of the heap leach field 110. Each section 116 may be elongated, perhaps having a length ranging between about 100 m and about 150 m, although other dimensions are also within the scope of the present disclosure. Each detector 120 may have a substantially rectangular footprint having lateral dimensions that may be proportional to the lateral dimensions of the section 116 of the heap leach field 110. The detectors 120 may be permanently, semi-permanently, or temporarily deployed within the heap leach field 110, and may be utilized in the generation of a density distribution of the field according to one or more aspects of the present disclosure.

[0033] The accuracy of muon radiography measurements within the scope of the present disclosure may be limited by the statistics of events measured at the detectors, i.e., by the number of muons measured at a given direction. The techniques described herein can be applied to a wide variety of scenarios where large-scale density distributions are desired. In general, increasing the surface area of each detector and/or the density of measurement points may increase the available count rate statistics and, thus, the sensitivity to the density in the region of interest.

[0034] The detectors 120 and/or 140 shown in FIGS. 1-3 may comprise scintillators in a variety of shapes. Finely segmented scintillation detectors such as scintillator fibers and/or other discrete members (hereafter collectively referred to simply as members) may, for practical purposes, be considered as independent sensors, and thus the loss of one channel may have a minimal impact on the overall performance of the detection system. As used herein, the term "scintillator member" includes any large aspect-ratio shapes of scintillator material, including but not limited to long strips of an optimized cross section of scintillator material. The scintillator members may comprise plastic scintillator material, inorganic crystal material, liquid-based scintillator material in an elongated shape, and/or a composite material, among others. In the case of a liquid-based scintillator material, the material may be sealed in an elongated shape, or may be free to flow in and out of an elongated channel. The cross-section of each scintillator member may be rectangular, elliptical, or any polygonal shape.

[0035] When ionizing radiation impacts a scintillator, an optical signal is generated. This light will propagate in the material, undergoing multiple reflections when scattering off the inner walls. Ultimately, scintillation photons will reach the entrance of an optical detector, which converts the light into an electrical signal. This process occurs over measurable time scales of a few nanoseconds per meter of optical path-length, depending on the detector properties, its geometry, and on how the light is coupled to the detector itself, among other possible factors. [0036] In a scintillator member as described above, optical photons emitted from a primary ionizing event will propagate in both directions along the member, and can be collected at both ends of the member with a pair of optical detectors. The relative difference in arrival times of the signal photons in the two detectors may be utilized as a measure of the relative position of where the primary ionization events occurred along the scintillator length. The sum of the arrival times may be a constant value, representing the total effective optical length of the scintillator.

[0037] Relative position accuracies of about 1 centimeter or better along the length of a scintillator member have been demonstrated for a variety of geometries. The particle or radiation traversal point is further constrained by the member finite transverse dimensions. By combining the measurements of multiple scintillating members or strips arranged in a bundle, the track or direction of the incoming radiation may be reconstructed.

[0038] Similarly, the cosmic ray muon traversal point in an elongated scintillator member such as a scintillator fiber may be determined by comparing the relative amplitude of the light signal at either end of the scintillator, i.e., based on a relative light attenuation measurement. The cosmic ray muon traversal point can also be determined by the common intersection volume between any one pair of scintillator members. A muon track or direction of the incoming radiation may be reconstructed using at least two such traversal points, or a combination of traversal points, obtained via overall time difference and/or light attenuation measurement.

[0039] FIG. 4 is a schematic view of a detector 175 representing an example implementation of the detectors 120 and/or 140 shown in FIGS. 1-3 according to one or more aspects of the present disclosure. The detector 175 may comprise a first planar array 180 of scintillator members and a second planar array 190 of scintillator members disposed above the first planar array 180. The first planar array 180 may comprise a first layer of elongated scintillator members 182 and a second layer of elongated scintillator members 184 that are transverse {e.g., orthogonal) to the scintillator members 182 within the first layer. Similarly, the second planar array 190 may comprise a first layer of elongated scintillator members 192 and a second layer of elongated scintillator members 194 that are traverse to the scintillator members 192 within the first layer.

[0040] The scintillator members 182, 184, 192, and/or 194 may each have a thickness ranging from less than about 1 mm to a few centimeters, and a length ranging between about 0.5 m and about 5 m, although other dimensions are also within the scope of the present disclosure. The planar arrays 180 and/or 190 may have lateral dimensions on the order of about 1 m, although other dimensions are also within the scope of the present disclosure. The upper planar array 180 may have a larger footprint than the lower planar array 190, such as by perhaps about 20%. The planar arrays 180 and 190 may be vertically separated by about 5 cm, although other dimensions are also within the scope of the present disclosure. Each layer of the arrays 180 and 190 may comprise any number of individual scintillator members 182, 184, 192, or 194, such that the example shown in FIG. 4 in which each layer comprises six scintillator members is not intended to be a limiting example. Each scintillator member 182, 184, 192, and/or 194 may be coupled at its ends to a single channel of a corresponding optical detector (not shown) or to corresponding single channel optical detectors.

[0041] In implementations utilizing the detector 175 shown in FIG. 4, or similar examples also within the scope of the present disclosure, cosmic ray muon trajectory may be determined based at least in part on the impact positions of detected cosmic ray muons within the first planar array 180 and the impact positions of detected cosmic ray muons within the second planar array 190. For example, cosmic ray muon impact positions detected within each of the first and second planar arrays may be determined based at least in part on the optical signals generated within at least two of the transverse intersecting elongated scintillator members 182, 184, 192, and/or 194.

[0042] The planar arrays 180 and 190 shown in Fig. 4 have a square shape. Other embodiments of the arrays may have different shapes, such as round, elliptical, rectangular, or any other polygonal shapes. Furthermore, the scintillator members 182, 184, 192, or 194 within each array can have a variety of different shapes. In some embodiments, the scintillator members have elongated shapes with square or rectangular profiles (e.g., as shown in Fig. 4). In other embodiments, the scintillator members are formed as square tiles or cubes.

[0043] FIGS. 5-7 show examples of scintillator members arranged in a collinear vertical bundle according to one or more aspects of the present disclosure. In FIG. 5, a detector unit 200 comprises a first multi-channel optical detector 210, a scintillator member bundle 208, and a second multi-channel optical detector 212. The detector unit 200 may be substantially similar to the detectors 120 and/or 140 shown in FIGS. 1-3 and/or the detector 175 shown in FIG. 4. The bundle 208 comprises a number of individual scintillator members such as members 220a, 220b, 220c, and 220d. The scintillator member diameter may range from less than about 1 mm to a few centimeters, for lengths ranging between about 0.5 m and about 5 m. Each bundle 208 may comprise as many as about 100 individual members. Each member is coupled at its top and bottom ends to a single channel of the optical detectors 210 and 212. The detectors 210 and 212 may also be or comprise a number of single channel optical detectors, which may be distributed at different or multiple locations.

[0044] When ionizing radiation (such as that of electrons, gammas, or muons) enters the scintillator bundle 208, such as the depicted muon track 230, it generates optical signals, such as optical signals 221a and 221b, whose travel times to each of the detector ends is dependent on the length of scintillator material traversed. The difference between the top and bottom arrival times correlates with the position of the ionization event impact point along the member. FIG. 6 shows a cross section of the detector unit 200 shown in FIG. 5. As shown, the muon track 230 crosses several of the individual members of the bundle 208. The transverse position is constrained by the transverse member or detector dimensions. In this way, multiple impact points can be correlated to a single reconstructed track.

[0045] For each event, the signal arrival time at each detector unit may be encoded according to well known time digitization techniques. The optical detectors 210 and 212 may be any optical amplification device. For example, a photo-tube, a semiconductor-based photo-diode, a photo-multiplier (such as Si-PMT (Si-photomultipliers)), a photomultiplier tube (PMT), a multichannel photomultiplier tube, a position sensitive photomultiplier tube, or a combination of one or more detectors each with one or more independent optical channels may be utilized for optical detectors 210 and 212.

[0046] For a given position resolution along the members, the track reconstruction accuracy may depend on the number of members producing a signal, and thus on the efficiency of light conversion. Each member hit determines an impact point, and two points are required to determine a trajectory. With more points, a more accurate reconstruction is possible and/or more advanced track reconstruction and/or data processing may be utilized, including signal-to-noise reduction techniques. The system of multiple members or strips can be arranged and/or packed in a number of ways in order to optimize the detection coverage.

[0047] The members may be thin enough to be flexible, and may be arranged in a variety of shapes, including a helix-like pattern so that members in different layers can cross at an optimized angle with respect to each other. For example, FIG. 7 shows another example detector unit 400 according to one or more aspects of the present disclosure, in which the members of a scintillator member bundle 408 are arranged around a hollow core 440. The detector unit 400 may be substantially similar to the detectors 120 and/or 140 shown in FIGS. 1-3, the detector 175 shown in FIG. 4, and/or the detector unit 200 shown in FIGS. 5 and 6, with the following possible exceptions.

[0048] The core 440 may house the digitizing electronics (not shown). The core 440 may also or alternatively comprise a fluid flow path, such as for the passage of one or more produced or injection fluids. The core 440 may also or alternatively house a Cerenkov detector, which may be sensitive to radiation emitted by deeply ultra-relativistic events and thus offer a convenient tag of cosmic-ray muons. The members may be layered in concentric circles or semicircles, including circles slightly offset from each other.

[0049] FIG. 8 shows another example detector unit 500 according to one or more aspects of the present disclosure, in which a set of scintillator members are arranged in a helically wound bundle. The detector unit 500 may be substantially similar to the detectors 120 and/or 140 shown in FIGS. 1-3, the detector 175 shown in FIG. 4, the detector unit 200 shown in FIGS. 5 and 6, and/or the detector unit 400 shown in FIG. 7, with the following possible exceptions. The detector unit 500 comprises a first multi-channel optical detector 510, a scintillator member bundle 508, and a second multi-channel optical detector 512. The bundle 508 comprises a number of individual scintillator members, such as members 570a, 570b, 570c, and 570d. Each member may be coupled at top and bottom ends to a single channel of the optical detectors 510 and 512. The members 570a, 570b, 570c, and 570d may be wound around a cylindrical core, such that the member 570a may be wound directly above the member 570d. The detectors 510 and 512 may also be or comprise a number of single channel optical detectors, which may be distributed at different or multiple locations.

[0050] FIG. 9 shows another example detector unit 600 according to one or more aspects of the present disclosure, in which a set of scintillator members are arranged in another helically wound bundle. The detector unit 600 may be substantially similar to the detectors 120 and/or 140 shown in FIGS. 1-3, the detector 175 shown in FIG. 4, the detector unit 200 shown in FIGS. 5 and 6, the detector unit 400 shown in FIG. 7, and/or the detector unit 500 shown in FIG. 8, with the following possible exceptions. The detector unit 600 comprises a first multi-channel optical detector 610, a scintillator member bundle 608, and a second multi-channel optical detector 612. The detectors 610 and/or 612 may also be or comprise a number of single channel optical detectors, which may be distributed at different or multiple locations.

[0051] The bundle 608 comprises scintillator members 680a, 680b, 680c, and 680d in a pattern similar to that shown in FIG. 8, although the helically wound members are arranged at a smaller angle with respect to the main axis of the detector unit 600. Layers of members may be wound around a central core at different angles or in an opposite direction (e.g. , in a mirror image to those shown in FIGS. 8 and 9), such as may provide multiple layers of members having a cross section similar to that shown in FIG. 7. One or more layers of windings as shown in FIG. 7 and/or 8 may be wound around a central core of vertically arranged members, such as shown in FIGS. 5 and 6.

[0052] FIGS. 10 and 1 1 show another example detector unit 700 according to one or more aspects of the present disclosure, in which a set of scintillator members are wound in a plane primarily perpendicular to the main axis of the detector unit 700. FIG. 1 1 is a cross-section of FIG. 10 along lines B-B' . The detector unit 700 may be substantially similar to the detectors 120 and/or 140 shown in FIGS. 1-3, the detector 175 shown in FIG. 4, the detector unit 200 shown in FIGS. 5 and 6, the detector unit 400 shown in FIG. 7, the detector unit 500 shown in FIG. 8, and/or the detector unit 600 shown in FIG. 9, with the following possible exceptions.

[0053] The detector unit 700 comprises a first multi-channel optical detector 710, a scintillator member bundle 708, and a second multi-channel optical detector 712. The detectors 710 and/or 712 may also be or comprise a number of single channel optical detectors, which may be distributed at different or multiple locations.

[0054] The bundle 708 comprises a number of individual scintillator members, such as members 790a, 790b, 790c, and 790d. Each member may be semi-circular and coupled at one end to a single channel of the optical detector 710 and at the other end to the optical detector 712. In this example, the members 790a, 790b, 790c, and 790d are wound around a cylindrical core 780, which may be substantially similar or identical to those described above.

[0055] According to one or more aspects of the present disclosure, the number of scintillator members, their position reconstruction accuracy, and/or their individual detection efficiencies may be optimized by choosing a value or a range values for their diameter and/or size and shape, such that the combined detection efficiency of the detector unit remains large enough to provide a sufficient event rate, and/or such that the signal-to-noise and/or track reconstruction capability may be optimized by having a larger number of hits. This may include bundles of members with unequal diameters, such as to maximize their packing density, or with unequal lengths, such as to optimize the packing of the optical read-out channels.

[0056] According to one or more aspects of the present disclosure, including any

combination of the examples and/or features described above, some of the scintillator members in the system may be collected together and coupled to a single multi-channel photo-detector, such as a segmented phototube or Si photo-multiplier.

[0057] Once one of the above implementations of long-range and/or deep-reading density monitoring technology based on the directional measurement of the underground cosmic ray flux is established, an estimation of the NPV of the heap may be generated. For example, by utilizing conventional tomographic techniques, the measured flux may be correlated to a local value of the heap bulk density, such as by relating the data measured over time to model predictions and/or baseline measurements, perhaps including those obtained prior to the introduction of production agents. This may result in a 3D bulk density distribution of the heap, which may highlight regions that have not been efficiently swept by the production agent, perhaps with greater accuracy and/or little systematic uncertainty relative to conventional techniques. The 3D bulk density distribution of the heap can be determined over a period of time. By analyzing the change in density distribution of the heap over time, the saturation of a fluid, such as a leachant fluid, and movement of the fluid through the heap can be monitored. The precision of such methods may depend on the statistical uncertainty with which the muon flux can be determined, and may thus be a function of measurement and/or observation time, reservoir depth, and/or the desired spatial accuracy of the directional information, among other factors.

[0058] Over time, the evolution of the density distribution may indicate the location and extent of by-passed zones, where no significant density change may have occurred due to insufficient flow of the production agent and/or inefficient collection of the produced fluids (e.g., saturated "pregnant" leachant solutions). Such inefficiencies may be attributable to, for example, the presence of impermeable zones, poor connectivity, fractures, and/or other obstacles. The NPV estimate of the heap may be improved by determining the volume of any such by-passed pay zones, such as by utilizing one or more nondestructive density monitoring techniques according to one or more aspects of the present disclosure. The NPV estimate may also or alternatively be improved by combining muon density tomography data with data from other sources, such as gravity, EM, and/or seismic surveys, and/or data from underground

measurements (such as temperature, pressure, density, resistivity, and/or nuclear spectroscopy, among others), which may facilitate a true multi-physics inversion. Such may be in contrast to conventional characterization techniques that depend on, or can be constrained by, accurate density data based on nuclear density measurements, which may suffer from limited depth of investigation and/or lack of true directional information. [0059] An NPV estimate as described above or otherwise within the scope of the present disclosure may be utilized to determine whether and/or what remedial actions may be considered and/or undertaken. Remedial action may be linked to an economic analysis, and

implementations according to one or more aspects of the present disclosure may facilitate better- informed and/or lower-risk decision-making.

[0060] Remedial actions may comprise adjustments to the production agent flow, such as to optimize production locally and/or to divert resources to more productive areas of the heap. Remedial actions may also or alternatively comprise changes in the composition of the production agent. Remedial actions may also or alternatively comprise stabbing additional leachant flow lines at various points in the heap, local injection of oxygen to facilitate and/or accelerate the mineral leaching chemistry, and/or increased or optimized acid concentration in the leachant fluid.

[0061] Improved NPV and/or field economics may also be achieved by limiting production costs via isolating unproductive zones, such as may comprise intentionally bypassing nonproductive zones. Implementations within the scope of the present disclosure may also be utilized by an operator to, for example, make informed decisions regarding reprocessing the heap, optimizing sweep profiles, and/or field abandonment, among others.

[0062] One or more aspects of the present disclosure may also regard an optimized workflow to maximize asset NPV. For example, the feasibility of cosmic-ray density measurements and their economical value may be determined utilizing forward modeling and integrated in a planning phase. An optimal configuration and deployment of the detector system may also or alternatively be determined. Cosmic-ray density data may be gathered, processed, and inverted to, for example, build customized density distributions that may be visualized or sliced in user- customizable ways and/or exported to other production management tools and models. Data may also or alternatively be correlated or combined with other measurements to, for example, perform multi-physics conditional inversions. Such processing may allow the asset operator to detect the need and overall economic value of a given remedial action or production optimization intervention.

[0063] Implementations within the scope of the present disclosure may also or alternatively pertain to identification of subterranean voids and/or with monitoring (over time) water encroachment and/or changing water tables. Such information may be utilized to assess and/or ensure the structural safety of underground tunnels and shafts (in both underground mining and in civilian engineering), as well as for optimizing excavation of such tunnels and shafts. In mining, there may be insufficient or inaccurate documentation regarding the location of previous tunnels or shafts. Implementations within the scope of the present disclosure, however, may allow an operator to detect the location of these voids and perhaps plan new tunnel trajectories, so as to minimize the risk of interception and/or tunnel collapse. Similarly, monitoring a water table may allow early indication of flooding that may affect the stability, integrity, and/or safety of underground excavations.

[0064] One or more aspects of the present disclosure may also or alternatively be utilized to determine water saturation in other types of heaps, such as coal, gravel, sand, and/or waste product, among others, including where such heaps may be exposed to rain, snow, and/or other atmospheric agents. Increasing water saturation may alter the weight of the heap, and may result in structural stability issues and/or agglomeration, cementation, and/or other transformations of the physical state of the heap material that may result in loss of NPV over time. Spatially sensitive density information as described herein may also be utilized as input for models and/or analyses to properly manage these and/or other types of risks.

[0065] FIG. 12 is a block diagram of an example processing system 1100 that may execute example machine-readable instructions to implement one or more aspects of the methods and/or processes described herein, and/or to implement the example heap leach field monitoring systems described herein. The processing system 1100 may be at least partially implemented in one or more of the detectors and/or surface equipment shown in the preceding figures. The processing system 1100 may be or comprise, for example, one or more processors, one or more controllers, one or more special-purpose computing devices, one or more servers, one or more personal computers, one or more personal digital assistant (PDA) devices, one or more smartphones, one or more internet appliances, and/or any other type(s) of computing device(s).

[0066] The system 1100 comprises a processor 1112 such as, for example, a general-purpose programmable processor. The processor 1112 may be substantially similar or identical to the processor 150 shown in FIG. 1. The processor 1112 includes a local memory 1114, and executes coded instructions 1132 present in the local memory 1114 and/or in another memory device. The processor 1112 may execute, among other things, machine-readable instructions to implement the methods and/or processes described herein. The processor 1112 may be, comprise or be implemented by any type of processing unit, such as one or more INTEL microprocessors, one or more microcontrollers from the ARM and/or PICO families of microcontrollers, one or more embedded soft/hard processors in one or more FPGAs, etc. Of course, other processors from other families are also appropriate.

[0067] The processor 1 1 12 is in communication with a main memory including a volatile (e.g., random access) memory 1 1 18 and a non- volatile (e.g., read-only) memory 1 120 via a bus 1 122. The volatile memory 1 1 18 may be, comprise or be implemented by static random access memory (SRAM), synchronous dynamic random access memory (SDRAM), dynamic random access memory (DRAM), RAMBUS dynamic random access memory (RDRAM) and/or any other type of random access memory device. The non- volatile memory 1 120 may be, comprise, or be implemented by flash memory and/or any other desired type of memory device. One or more memory controllers (not shown) may control access to the main memory 1 1 18 and/or 1 120.

[0068] The processing system 1 100 also includes an interface circuit 1 124. The interface circuit 1 124 may be, comprise, or be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB) and/or a third generation input/output (3GIO) interface, among others.

[0069] One or more input devices 1 126 are connected to the interface circuit 1 124. The input device(s) 1 126 permit a user to enter data and commands into the processor 1 1 12. The input device(s) may be, comprise or be implemented by, for example, a keyboard, a mouse, a touchscreen, a track-pad, a trackball, an isopoint and/or a voice recognition system, among others.

[0070] One or more output devices 1 128 are also connected to the interface circuit 1 124. The output devices 1 128 may be, comprise, or be implemented by, for example, display devices (e.g., a liquid crystal display or cathode ray tube display (CRT), among others), printers and/or speakers, among others. Thus, the interface circuit 1 124 may also comprise a graphics driver card.

[0071] The interface circuit 1 124 also includes a communication device such as a modem or network interface card to facilitate exchange of data with external computers via a network (e.g., Ethernet connection, digital subscriber line (DSL), telephone line, coaxial cable, cellular telephone system, satellite, etc.).

[0072] The processing system 1 100 also includes one or more mass storage devices 1 130 for storing machine -readable instructions and data. Examples of such mass storage devices 1 130 include floppy disk drives, hard drive disks, compact disk drives and digital versatile disk (DVD) drives, among others. [0073] The coded instructions 1 132 may be stored in the mass storage device 1 130, the volatile memory 1 1 18, the non-volatile memory 1 120, the local memory 1 1 14 and/or on a removable storage medium, such as a CD or DVD 1 134.

[0074] As an alternative to implementing the methods and/or apparatus described herein in a system such as the processing system of FIG. 12, and/or in addition thereto, one or more aspects of the methods and or apparatus described herein may be embedded in a structure such as a processor and/or an ASIC (application specific integrated circuit).

[0075] FIG. 13 is a flow-chart diagram of at least a portion of a method 1200 according to one or more aspects of the present disclosure. The method 1200 may be performed utilizing the apparatus/systems shown in one or more of FIGS. 1 -12. The method 1200 comprises detecting (at 1210) cosmic ray muon impacts within a heap leach field, such as the heap leach field 1 10 shown in FIGS. 1-3. Such detection may utilize any one or more of the detectors described above or otherwise within the scope of the present disclosure. The detected muon data is then utilized to determine (at 1220) the density of the heap leach field at a plurality of locations within the field, such as by operation of a processor in communication with one or more of the detectors. Such processor may be substantially similar or identical to the processor 150 shown in FIG. 1 and/or the system 1 100 shown in FIG. 12. A density distribution may then be determined (at 1230) based on the densities determined at the plurality of locations within the heap leach field. The density determined at each of the plurality of locations, and/or the density distribution determined based on the density data, may utilize any known or future-developed radiation, particle, and/or charged particle transport algorithm. One or more simulation algorithms may also or alternatively be employed, such as the well known Monte Carlo simulation, among others. The method 1200 may also comprise assessing the NPV (at 1240) of the heap leach field based on the density distribution. For example, the NPV of the heap leach field may be proportional to the materials produced by the heap leaching process, which may be proportional or otherwise related to the previously density data. For example, the NPV of the heap leach field may be proportional to the materials produced by the heap leaching process, which may be proportional or otherwise related to the previously obtained density data. More specifically, saturation of a fluid (e.g., a leachant fluid ) within the heap is determined based on the density distribution. The net present value of the heap can then be determined based on the saturation of the fluid within the heap. [0076] In view of all of the above and the figures, a person of ordinary skill in the art should readily recognize that the present disclosure a system comprising: a plurality of cosmic ray muon detectors each positioned to detect cosmic ray muons that traverse a heap and operable to generate a signal in response to cosmic ray muons that impact the detectors; and a processor operable to generate a density distribution of a portion of the heap based on the signals generated by the plurality of cosmic ray muon detectors. At least some of the plurality of cosmic ray muon detectors may be positioned within the heap.

[0077] The plurality of cosmic ray muon detectors may comprise a plurality of scintillator detectors. Each scintillator detector may comprise: at least one scintillator member operable to generate an optical signal in response to cosmic ray muons that impact the scintillator member; and an optical detector optically coupled to the at least one scintillator member and operable to detect the optical signal generated by the at least one scintillator member. Each scintillator detector may comprise a plurality of scintillator members. The plurality of scintillator members may comprise a bundle of helically wound scintillator members.

[0078] The system may further comprise: a first optical detector optically coupled to a first end of each of the plurality of scintillator members; and a second optical detector optically coupled to a second end of each of the plurality of scintillator members; wherein the processor may be operable to determine detected cosmic ray muon impact positions along each of the plurality of scintillator members based at least in part on a comparison of optical signal arrival times at the first and second optical detectors.

[0079] The processor may be further operable to determine detected cosmic ray muon trajectory information based at least in part on the determined impact positions of detected cosmic ray muons impacting at least two of the plurality of scintillator members. The optical detector may be optically coupled to each of the plurality of scintillator members, and the optical detector may comprise a plurality of independent optical amplification channels each optically coupled to a corresponding one of the plurality of scintillator members. The optical detector may be selected from the group consisting of: a solid-state optical detector, a photo-diode, a solid- state photo-multiplier, electron avalanche optical detector, and a multi-channel plate type optical detector.

[0080] The plurality of scintillator members may comprise: a first planar array of scintillator members; and a second planar array of scintillator members disposed above the first planar array of scintillator members. The processor may be further operable to determine cosmic ray muon trajectory based at least in part on: impact position of detected cosmic ray muons within the first planar array of scintillator members; and impact position of detected cosmic ray muons within the second planar array of scintillator members. Each of the first and second planar arrays may comprise a first layer of elongated scintillator members and a second layer of elongated scintillator members that are traverse to the elongated scintillator members within the first layer. The processor may be further operable to determine detected cosmic ray muon impact positions within each of the first and second planar arrays based at least in part on the optical signals generated within at least two transverse intersecting elongated scintillator members.

[0081] The present disclosure also introduces a method comprising: detecting cosmic ray muons that traverse a heap using a plurality of cosmic ray muon detectors positioned within a heap leach field; determining density of the heap at a plurality of locations within the heap based on the detected cosmic ray muons; and determining a density distribution of a portion of the heap based on the determined density at each of the plurality of locations. The method may further comprise determining the density distribution of the portion of the heap over time. The method may further comprise monitoring saturation of a fluid within the heap using the density distribution determined over time. Determining density of the heap at each of the plurality of locations may comprise determining trajectories of the detected cosmic ray muons impacting each of the plurality of cosmic ray detectors.

[0082] The method may further comprise assessing a net present value (NPV) of the heap based on the density distribution. The method may further comprise: determining an appropriate remedial action based upon the density distribution; and performing the appropriate remedial action.

[0083] The present disclosure also introduces a system comprising: a plurality of cosmic ray muon detectors each positioned within a heap leach field and operable to generate an optical signal in response to cosmic ray muons detected within the heap leach field; and a processor operable to generate a density distribution of a substantial portion of the heap leach field based on the optical signals generated by the plurality of cosmic ray muon detectors. The system may further comprise a plurality of cosmic ray muon detectors coupled to at least one optical detector operable to generate an additional signal based on the scintillation signals generated by the plurality of cosmic ray muon detectors, wherein the processor may be operable to generate the density distribution based on the additional signal. The system may further comprise a plurality of optical detectors each optically coupled to a corresponding one of the plurality of cosmic ray muon detectors and operable to generate an output signal based on the optical signal generated by the corresponding one of the plurality of cosmic ray muon detectors, wherein the processor may be operable to generate the density distribution based on the output signals generated by each of the plurality of optical detectors.

[0084] At least one of the plurality of cosmic ray muon detectors may comprise a plurality of scintillator members each operable to generate an optical signal in response to cosmic ray muons detected within the heap leach field. The plurality of scintillator members may comprise a bundle of helically wound fibers or other elongated scintillation members. Such system may further comprise: a first optical detector optically coupled to a first end of each of the plurality of scintillator members; and a second optical detector optically coupled to a second end of each of the plurality of scintillator members; wherein the processor may be operable to determine detected cosmic ray muon impact positions along each of the plurality of scintillator members based at least in part on a comparison of optical signal arrival times at the first and second optical detectors or on the common intersection between pairs of scintillation members. The processor may be further operable to determine detected cosmic ray muon trajectory information based at least in part on the determined impact positions of detected cosmic ray muons impacting at least two of the plurality of scintillator members.

[0085] The system may further comprise an optical detector optically coupled to each of the plurality of scintillator members, wherein the optical detector may comprise a plurality of independent optical amplification channels each optically coupled to a corresponding one of the plurality of scintillator members. The optical detector may be or comprise a solid-state optical detector, a photo-diode, a solid-state photo-multiplier, an electron avalanche optical detector, and/or a multi-channel plate type optical detector.

[0086] The system may further comprise a plurality of communications links each extending between the processor and a corresponding one of the plurality of cosmic ray muon detectors.

[0087] The present disclosure also introduces a method comprising: detecting cosmic ray muons impacting each of a plurality of cosmic ray muon detectors positioned within a heap leach field; determining density of the heap leach field at a plurality of locations within the heap leach field based on the detected cosmic ray muons; and determining a density distribution of a substantial portion of the heap leach field based on the determined density at each of the plurality of locations. Determining the density of the heap leach field at each of the plurality of locations may comprise determining trajectories of the detected cosmic ray muons impacting each of the plurality of cosmic ray detectors. The method may further comprise assessing a net present value (NPV) of the heap leach field based on the density distribution.

[0088] The foregoing outlines features of several embodiments so that those skilled in the art may better understand the aspects of the present disclosure. Those skilled in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and/or achieving the same aspects introduced herein. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions and alterations herein without departing from the spirit and scope of the present disclosure. For example, although the preceding description has been described herein with reference to particular means, materials and embodiments, it is not intended to be limited to the particulars disclosed herein; rather, it extends to functionally equivalent structures, methods, and uses, such as are within the scope of the appended claims.

[0089] The Abstract at the end of this disclosure is provided to comply with 37 C.F.R.

§ 1.72(b) to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.