Fully populated energy volume for determining the permeability field

Abstract

Provided herein are methods for mapping a permeability field architecture of a study volume in country rock by acquiring seismic trace data from a network of seismic sensors above the study volume and calculating from the seismic trace data, over a series of time intervals, a signal energy value, a coherent energy value and a semblance value for the voxels of the study volume. An energy sub-volume of the study volume (called the full activity volume or FAV) is determined by identifying all voxels of the study volume having a semblance value and signal energy and coherent energy values that meet a specified active voxel threshold condition. From the FAV the architecture of the permeability field of the study volume can be mapped.

Description

LVM Ref.340101: 76-24 WO FULLY POPULATED ENERGY VOLUME FOR DETERMINING THE PERMEABILITY FIELD BACKGROUND OF INVENTION

[0001] It is desirable to accurately locate permeability zones and fracture networks within a study volume without incurring the expense of drilling. It is also desirable to accurately forecast well production without incurring the expense of drilling. Current methods for locating such zones involve time consuming, complex and expensive means such as 3D seismic (Brown, A. R. (1991), subsurface mapping, stratigraphic and lithologic analysis (North, F.K., 1985), geo-mechanical analysis (Zoback, 2011) and numerous other disciplines for mapping and analyzing a reservoir. An example of the work involved is that of Michelena et al (2019). There is a need in the art for improved forecasting methods to optimize fluid recovery and targeting sub-surface regions for optimal placement of geothermal systems, CO2 sequestration, energy storage systems and other climate mitigation solutions.

[0002] US Pat. Pub. No.2022 / 0136382 (Atty Ref.338972: 100-20 US) titled “Methods for Positioning a Well for Optimal Fluid Production” (Geiser et al.) relies on semblance values of voxels within a study volume to identify NWA voxels with sufficiently high semblance for locating and monitoring wells for optimized fluid production. Provided herein are improved methods for locating a well bore for fluid recovery using semblance and an energy-based parameter. The improvements relate to use of a physical state variable (e.g., energy or an energy-related parameter) rather than rely solely on a statistical parameter, such as semblance. Disclosed herein is evidence that energy (such as signal energy and coherent energy) in combination with semblance, instead of semblance alone, can be used to provide a more detailed and accurate mapping of the permeability field as well as fracture networks and other physical attributes, with attendant benefits associated with determination of a physical state variable, such as an energy value, for each voxel. SUMMARY

[0003] Provided herein is a method for the creation and analysis of an energy volume that is a study volume of voxels, each voxel of the study volume containing a time-varying signal energy and coherent energy data streams along with the corresponding semblance data stream. Such an analysis of an associated full activity volume (FAV) provides the ability to obtain the permeability field of the study volume. Analysis of the semblance and the signalLVM Ref.340101: 76-24 WO energy and coherent energy data streams provides the ability to examine the dynamic response of the voxel to the changing stress field, illuminating such phenomena as the resonance response to passing seismic wave fronts. In particular, calculating coherent energy, while related to the semblance calculations, relies on a distinct methodology. Similar to US Pat. No.7,127,353, which is specifically incorporated by reference herein for the methods described therein, provided herein are methods for determining or imaging a permeability field of a FAV. The instant methods, however, additionally rely on a coherent energy value associated with each voxel, including a time-varying coherent energy. Coherent energy is a more realistic measure of the actual emission of energy from the voxel rock than semblance and / or signal energy. Use of the coherent energy provides for: a more precise delineation of the permeability fields than attainable using semblance and / or signal energy alone; a more accurate picture of the dynamics of the permeability field in response to the changing stress environment; a more direct measure of the resonance phenomena of the rock energy emissions; an improvement in the targeting of well bores for applications in geothermal field development, CO2 sequestration, sub-surface energy storage systems, as well as for fluid extraction, over that attainable using semblance and / or signal energy alone. Also provided herein is a method for locating a well bore for high fluid recovery, including recovery of liquids and / or gases, similar to US Pat. Pub. No.2022 / 0136382 but uniquely enhanced by the use of coherent energy in the definitions of active voxels and of near-well active voxels. US Pat. Pub. No.2022 / 0136382 titled “Methods for Positioning a Well for Optimal Fluid Production”) is specifically incorporated by reference herein. The method may comprise acquiring an energy volume for a reservoir of interest. As described herein, a coherent energy-based parameter is associated with each voxel of the FAV.

[0004] Provided are methods for mapping a permeability field architecture of a study volume in country rock by: acquiring seismic trace data from a network of seismic sensors above the study volume; calculating from the seismic trace data, over a series of time intervals, a voxel signal energy value, a coherent energy value and a semblance value for each voxel in the study volume; specifying an active voxel threshold condition to define a FAV of the study volume. From this, permeability field maps of the study volume may be obtained. To locate zones of high permeability, a high activity permeability field (HaPF) within the FAV is determined comprising those voxels, which satisfy the further constraint of a high activity threshold condition. The architecture of the FAV and the HaPF is determined by the application of various coherent energy surface extraction and contouring methods suchLVM Ref.340101: 76-24 WO as isosurface extraction and skeletonization and color contouring of the voxel coherent energy values. In this manner, the permeability field architecture of the study volume is mapped. This mapping of the permeability field architecture in the study volume, including the 3D location of relatively high permeability zones, has a number of uses, including uses to mitigate climate change (e.g., location of CO2 sequestration prospects, improved methods to site enhanced geothermal systems), improve fluid recovery from the Earth, and improved location and monitoring of wells as well as monitoring of seismic events due to fluid extraction and well bore stimulation.

[0005] The step of calculating for each voxel of the study volume the signal energy and coherent energy values and the semblance values may comprise calculating for a series of time intervals, the signal energy data stream of the stacked focused trace of the voxel's trace ensemble, and the corresponding coherent energy and semblance data streams.

[0006] Exemplary formulas for the calculating steps are provided herein, including the voxel signal energy that is calculated from the signal energy of the voxel’s aperture stack trace over a specified time interval (the semblance time window). The aperture stack trace is defined by (EQ 1) ^^^^^^^^ ൌ: ^∑^^ൌ^^^^^^ൌ1 ^^^^^i^^.trace ensemble and ^^ is the trace index. Define the signal energy E^^^^ of the aperstack trace to be: (EQ 2) ^^^^^^ ൌ:∑^ୀ^ൈ^^ାேೞି^ ^^^^^^^^^^ଶ^ୀ^ൈ^^ .The energy of the aperture stack trace of the voxel over a specified time interval, and the product of the number of traces in the aperture stack trace times the stack of the signal energies of the voxel's individual aperture traces over the specified time interval. The standard semblance equation (Neidell and Taner, 1971): ∑^సೖൈೞ^శಿೞషభ ^∑^సಿ^^స ்^ ^୧^ ^మ(EQ 3) ^^^^^^^సೖൈೞ^భ , for ^^ 0,1,....LVM Ref.340101: 76-24 WO Equation EQ 3 shows that the calculated semblance can also be considered as a normalize signal energy of the aperture stack trace. Its values can be shown to lie within the interval [0.0,1.0].

[0007] The changes in the stress field comprise changes in the transient and induced stress fields in the study volume. The methods provided herein have broad applicability, including the ability to map the permeability field with or without active (human) induced seismic events. Similarly, depending on the application of interest, the methods are compatible with a range of study volume types. For example, the study volume may correspond to a reservoir of interest, a geological formation (e.g., a stratigraphic or lithostratigraphic unit, etc.); a target volume for a geothermal system, a target volume for a CO2 sequestration system, a target volume for an energy storage system, a waste water injection site, etc.

[0008] The methods are compatible with a study volume that includes fracture systems and zones of high energy emission.

[0009] The network of seismic sensors may comprise a geophone array located to detect seismic emissions from the study volume underneath the array.

[0010] Any of the methods may further comprise the step of introducing a seismic energy perturbation, such as through hydraulic stimulation or other stimulation methods.

[0011] The step of obtaining the architecture of the permeability field may comprise applying one or more attribute extractive techniques. Exemplary attribute extraction techniques include, color contouring, isosurface extraction, and skeletonization of the FAV voxel coherent energy values.

[0012] The methods provided herein may further comprise the step of determining a maximum number of NWA voxels connected to a well bore or proposed well bore location. Identifying a maximum number of NWA voxels has a range of usages where a high permeability region is desired to be located without any preemptive drilling or the like. For example, the methods may further comprise the step of: identifying an optimal well bore location corresponding to a region having the high permeability for the purpose of, for example, developing an Enhance Geothermal Systems (EGS), CO2 Sequestration Systems (CO2SS), Energy Storage Systems (ESS), or a Waste Water Injection Site (WWIS);LVM Ref.340101: 76-24 WO identifying the NWA voxels in contact with or indirectly in contact with an operating well bore for the purpose of, for example, monitoring the effects of stimulation and / or production.

[0013] The methods may further comprise the step of locating a sub-volume of the study volume suitable for fluid / gas-storage or the step of extracting heat from a thermal exchange fluid flowing into and out of the located sub-volume of the study volume to be used in a geothermal process.

[0014] The step of acquiring the seismic trace data may comprise using one or more of: a 3D seismic survey; a geophone surface array; a geophone buried array; or any combination thereof.

[0015] The method may be used for a fluid recovery from country rock, including a fluid comprising hydrocarbons (oil or gas) or water.

[0016] Depending on the desired accuracy of the permeability field mapping, and specifications of the seismic sensors, a voxel volume is specified for the study volume. For example, the voxel volume may be between 100 m3and 10ଽm3.

[0017] The size of the study volume depends on the application of interest. The size of the volume may have a range between 0.1 km3to 1000 km3.

[0018] The method may further comprise the step of drilling a well bore in the study volume at a location corresponding to a region with highest maximum number of NWA voxels in contact with a proposed well bore location.

[0019] The step of acquiring the FAV may comprise acquiring the seismic trace data for a period of time ranging up to 24 hours and optionally at a sampling rate of between 1 Hz and 1 kHz.

[0020] The seismic trace data may be obtained over a time range that is between 1 second and 100 days, and any subranges thereof.

[0021] To help delineate the architecture of the HaPF within a FAV, the user may extract isosurfaces of the coherent energy and / or apply other feature extractive technologies to reveal the architecture of the HaPF. A user may exert control over the HaPF, by relaxing or tightening the specified high activity threshold condition.LVM Ref.340101: 76-24 WO

[0022] Without wishing to be bound by any particular theory, there may be discussion herein of beliefs or understandings of underlying principles relating to the devices and methods disclosed herein. It is recognized that regardless of the ultimate correctness of any mechanistic explanation or hypothesis, an embodiment of the invention can nonetheless be operative and useful. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] FIG.1: First use of SET to image crustal activity (Cusiana and Cupiaga Fields, Columbia, circa mid 1980s). The two figures cover a two-hour period, showing dislocation creep on a tear bounded thrust at a depth of 20 km.

[0024] FIG.2: An illustration of a spectrogram of a voxel's stacked focus trace exhibiting 42 Hz resonance after a mine blast event.

[0025] FIG.3: An illustration of scaled wavelets and how they are used in the process of wavelet analysis of a signal data stream to reveal the time-dynamics of the frequency components of the data stream.

[0026] FIGs.4A-4C: Wavelet analysis of seismic data from a mine blast near a RGP gas field. The voxel depth is 4200 feet. FIG.4A is a wavelet analysis of the signal energy of the stacked focused trace. FIG.4B is a wavelet analysis of the semblance of the voxel's trace ensemble. Note that the semblance values in FIG.4B do not accurately track the signal energy emissions displayed in FIG.4A. FIG.4C is a zoomed-in portion of FIG.4A covering the blast followed by 30 seconds of resonance. This reveals a complex resonance response of the rock fabric over a thirty second period after the mine blast event past through the geophone array field.

[0027] FIGs.5A-5B: Wavelet analysis of a voxel's semblance and signal energy from the mine blast recorded by geophone array in an RGP gas field. In these figures, the voxel depth is 4200 feet and the time interval 1.75 minutes starting at 17:23:00. The vertical axis is frequency (Hz). Time moves from left to right on the horizontal axis and the hotter the color the higher the wavelet coefficient value indicating the intensity of the frequency component in the semblance or energy signal values. The lower strip displays the corresponding semblance or energy values. FIG.5A is a wavelet analysis of semblance of the voxel's trace ensemble. FIG.5B is a wavelet analysis of the signal energy of the voxel's aperture stack trace.LVM Ref.340101: 76-24 WO

[0028] FIG.6: The architecture of a synthetic seismic trace T^. t^through t^mark the beginning and end times of each segment of the synthetic trace described in the figure. The bottom display shows a wavelet analysis of the semblance of an ensemble of synthetic traces. In this case, in the frequency variation section, the frequencies of Sinus2 are left unchanged. The vertical axis is frequency and the horizontal axis is time.

[0029] FIG.7: The wavelet analysis of an ensemble of synthetic seismic trace. Both the semblance (top trace) and signal energy (bottom trace) are displayed. In the upper portion of each image, the wavelet coefficient is color contoured, highlighting the dynamics of the frequency components of the corresponding data. In the lower portion of each image is a plot of the data being analyzed. For these two examples, the synthetic traces vary the frequencies and amplitudes of the sinusoidal functions throughout the frequency variation section. A comparison between the semblance data and signal energy data shows that while the semblance data identifies the frequency variation section as having low semblance, the signal energy doesn't make this distinction. On the other hand, the semblance data does not track the large increase in signal energy during the energy blast section seen in the signal energy display.

[0030] FIG.8: A plot of coherent energy verses semblance from data generated by the Synthetic Trace Ensemble System, showing the quadratic relationship between coherent energy and semblance.

[0031] FIG.9: A plot of coherent energy verses signal energy from data generated by the Synthetic Trace Ensemble System, showing the quadratic relationship between coherent energy and signal energy.

[0032] FIG.10A: A plot of signal energy verses semblance from data generated by the Synthetic Trace Ensemble System, showing the linear relationship between signal energy and semblance. FIG.10B: ^^^^^^ denotes percentage of coherent energy to signal energy. That is,^^^^^^ ൌ ^^^ / E where ^^^ denotes coherent energy and ^^ denotes signal energy of a voxel'strace ensemble. The figure shows a plot of ^^^^^^ as a function of semblance from a study's trace ensemble generated by the Synthetic Trace Ensemble System. The graph shows the quadratic relationship between ^^^^^^ and semblance. Note that ^^^^^^ is about 0% when semblance is around 49%. That is, in this particular study, the non-coherent traces of the trace ensemble have an almost 50% semblance value. FIG.10C: Schematic diagram illustratingLVM Ref.340101: 76-24 WO the user-assigned semblance constraints ^^^, ^^^and corresponding coherent energy percentage (^^^^^^) constraints ^^^, ^^^that can be used to specify a quadratic coherent energy percentagefunction, ^^^^^^ ൌ ^^^ா^^^^^, used to compute the coherent energy ^^^ of a voxel's traceensembleto semblance value ^^, namely ^^^ ൌ ^^^ா^^^^^ ൈ ^^ where ^^ is thesignal energy of the voxel's trace ensemble.

[0033] FIG.11: A map highlighting the relative locations of the RGP geophone array for SET data gathering and processing during mine blast activity from active mining sites. The voxel lies within the geophone array field.

[0034] FIG.12: A chair cut of a 3D full activity volume (FAV) showing areas of LaPF and areas of HaPF.

[0035] FIG.13: A chair cut of a 3D full activity volume (FAV) showing the HaPF skeletonized surfaces within the FAV.FIGs.14-15: Comparison of four-dimensional (4-D) seismic data and permeability field imaging (PFI) data from a mine flood inflow site showing a direct correspondence between the location of fluids indicated by 4-D seismic (FIG.14) and regions of high semblance value (FIG.15). The data sets are superposed on the mine working. SET = seismic emission tomography.

[0036] FIG.16: A chair-cut of a Barnett full activity volume (FAV) showing high- activity permeability field semblance clouds and the proposed interpretation of semblance value gradients. Here, the lower semblance gradients are interpreted to represent volumes of higher bulk permeability (k) (hot colors) and higher semblance gradients lower k (cool colors). Courtesy of Burlington Resources; credit: R. Scammel.

[0037] FIG.17: From a case study of the SET imaging technique and skeletonization of NWA voxels illustrating how these techniques are used to monitor wells during stimulation and showing the resulting fracture propagation from the stimulated well to a nearby monitoring well.

[0038] FIG.18: Semblance mapping showing the activation of a natural fracture network caused by a single-stage frac along a well bore.LVM Ref.340101: 76-24 WO

[0039] FIG.19 Permeability mapping showing successive unpacking of semblance isosurfaces in the Barnett Shale by successively increasing the minimum semblance value displayed.

[0040] FIG.20: A permeability field map showing a reservoir seal and that no product operations affect surface groundwater aquifers.

[0041] FIG.21: A flow-chart summary of a method for mapping a permeability field. DETAILED DESCRIPTION OF THE INVENTION

[0042] In the following description, numerous specific details of the devices, device components and methods of the present invention are set forth in order to provide a thorough explanation of the precise nature of the invention. It will be apparent, however, to those of skill in the art that the invention can be practiced without these specific details.

[0043] In general, the terms and phrases used herein have their art-recognized meaning, which can be found by reference to standard texts, journal references and contexts known to those skilled in the art. Certain terms specifically relevant to the technology provided herein have definitions provided herein to further clarify their specific use in the context of the claimed invention.

[0044] Many of the following terms have been introduced in recently published papers and are not yet in the common parlance of the geological / seismological community. They are introduced here as further clarification. Further details and examples are provided in the Summary and the Detailed Description of the Invention and in the context of the claims.

[0045] The term "Study Volume" refers to any sub-surface volume of rock such as a geologic formation, a reservoir, a target volume for "Enhance Geothermal Systems" (EGS), “CO2 Sequestration Systems" (CO2SS), "Energy Storage Systems" (ESS), "Waste "Water Injection Site" (WWIS), etc.

[0046] The term "Transient Stress Field" refers to the stress field that is the product of continual small perturbations by transient natural loadings due to such things as air mass movements, ocean wave impacts, Earth tides, passing teleseismic waves, etc.

[0047] The term "Induced Transient Stress Field" refers to the stress field that is the product of human activity and can be directly correlated with it.LVM Ref.340101: 76-24 WO

[0048] The term “Seismic Emission Tomography” or “SET” refers to the collection and analysis of seismic waves from sources within a study volume to provide information about the study volume. SET monitors changes in seismic energy emission due to changes in transient and induced transient stress field to generate data relating to mechanical properties of the study volume, including permeability.

[0049] The term "Data Stream" refers so any indexed time series D(i), with sample rate δ (time between samples in seconds). If t_0 is the starting time, then the index i corresponds totime ^^ ൌ ^^^ ^ ^^ ൈ ^^, for ^^ ൌ 0,1,2,⋯.

[0050] The term "Data Stacking Method' or "Stacking Method" refers to a method of combining values of consecutive, uniform-length segments of a data stream, D(i), thereby forming a new data stream S(D,k). The length, N, of the segments is called the "Stacking Size" of the method. If δ is the sample rate of the original data stream D(i), then N×δ is the sample rate of the stacked data stream S(D,k). S(D,k) is referred to as a N×δ-second stack. Examples of stacking methods include a. "Sum Stack" S^D, ^^^ ൌ ∑^ ୀ ^^ேା^^ି^^ ୀ ^ே ^^^^^^ ;1^;

[0051] with the stacking method, referred to as the "Stacking Statistic" or "Stacking Method'sStatistic", calculated from the stack values ^D^i^|i ൌ ^^^^, ... , ^^^^^ ^ 1^ െ 1^.. For examplestat(D,k) might be the standard deviation of the values, the variance, the mode, etc.

[0052] The data stream itself can be considered to be trivially stacked, with stacking size 1. Note that the values of a stacked data stream may be further subjected to stacking. For example, the first stack might be a 1-second stack which might be further stacked to a create 1-minute stack, combining 601-second stacks, etc.

[0053] The term “Voxel” refers to a uniformly sized three-dimensional volume of rock, such as a rectangular or cuboid volume, together with its location, dimensions, and associated data. A study volume may be considered to be subdivided into a 3-dimensional grid ofLVM Ref.340101: 76-24 WO uniformly sized voxels. The methods provided herein are compatible with any number of voxels and any size range of voxels, depending on the application of interest. For example, a volume of a voxel includes, but is not limited to, a range of between 100 m3and 109m3, for a study volume of between, for example, 0.1 km3and 1000 km3, with a corresponding total number of voxels defined as the ratio of Study Volume to Voxel Volume. To maximize the resolution of the permeability mapping, it is preferable to make the total number of voxels as large as computationally feasible and consistent with geophysical constraints.

[0054] The term "Voxel Aperture" refers to the appropriate seismic migration aperture (a region above the voxel for the gathering of seismic signals) given the depth of the voxel. The term "Voxel's Trace Ensemble" refers to the seismic traces gathered by geophones within the voxel's aperture and focused on the voxel's location. The term "Aperture Trace" refers to a trace in a voxel's trace ensemble. Included in the data associated with a voxel is the voxel's trace ensemble, semblance data, energy data, or other calculated values indicating, for example, permeability and other natural features of its location.

[0055] The term "Aperture Stack Trace" (also called the "Stacked Focused Trace") of a voxel refers to a trace AS[i] formed by summing the ithvalues of all the traces in the Voxel'strace ensemble. The aperture stack trace is defined as ^^^^^^^^ ൌ ∑௫ୀே^௫ୀ^ ^^௫^^^^, where Txis the xthaperture trace, Nt is the number of traces in the voxel's a trace sampleindex also called a time index.

[0056] The term “Fluid Reservoir” refers to a geologic formation containing one or more fluids embedded or trapped within the formation.

[0057] The term "Semblance" refers to a measure of the coherence or similarity of the seismic traces in a voxel's trace ensemble over a specified interval of time referred to as the "Semblance Time Window". Semblance values of a voxel may either be a single semblance value or a data stream of semblance values calculated over a series of successive time intervals.

[0058] The term "Signal Power", P(k), over an index time window of length N of a data stream D(i), is defined as the sum of the squares of D(i) divided by N, that is:^^^^^^ ൌ ^ ∑^ୀ^ାேି^^ୀ^ ^^^^^^ଶ .LVM Ref.340101: 76-24 WO

[0059] The term "Signal Energy", E(k), over an index time window of length N of a data stream D(i), is defined the power P(k) multiplied by the time interval N, or^^^^^^ ൌ ∑^ୀ^ାேି^ ଶ^ୀ^ ^^^^^^ .

[0060] The term "Energy" refers to the variation of the energy emitted from rock over time as it responds to the changing stress environment. Energy-related physical properties such as power or work in reference to the response of rock to its changing stress environment are derivable from energy and therefore their use is equivalent to energy as used herein. For example, the physical parameter power is equal to energy divided by the time over which the energy is expended while the physical parameter work is equal to the change of energy over time. Therefore, in the context of a voxel's energy time stream, any conclusion about or use of parameter energy herein is easily transferred to the physical parameters power or work.

[0061] The term "Signal Energy of a Voxel" or "Voxel Signal Energy Value" refers to the signal energy value calculated from the voxel's aperture stack over the semblance time window. The signal energy values of a voxel form a data stream parallel to the semblance data stream.

[0062] The term "Coherent Energy of a Voxel" refers to that portion of the signal energy of the voxel corresponding to the energy emitted from the voxel rock. Note that the traces of the voxel's trace ensemble energy may contain signal energy corresponding to various source of noise not connected to the actual energy emission from the voxel rock. The methods herein apply to any definition of the concept of coherent energy of a voxel. For the purposes of specificity, coherent energy of a voxel may be defined herein as the signal energy value of the stack of the coherent traces of the voxel's trace ensemble calculated over the semblance time window. Coherent energy is typically a fraction of the signal energy. The relationship between semblance, signal energy and coherent energy is further discussed below.

[0063] A "Coherent Energy Function", ^^ ^^^,^^^, is any user-defined function which^ாcalculates the voxel's coherent energy over the semblance time window in which the voxel's semblance S and signal energy E were calculated. It must be monotonic increasing in thevoxel's semblance and signal energy. That is, if S1≥S and E1 ≥E then ^^ ^^^1,^^1^ ^^ா^^ ^^^,^^^. It also must satisfy the condition: ^^ ^^^,^^^ ^ ^^. A coherent energy function can^ா ^ாbe used to generate a coherent energy data stream in parallel with the corresponding semblance and signal energy data streams. Note that a coherent energy function mayLVM Ref.340101: 76-24 WO incorporate properties of the study volume (such as lithology) as well as data associated with the voxel in addition to the voxel's aperture ensemble and semblance and signal energy.

[0064] A study volume has stacking methods associated with each of its data streams. The data streams associated with a voxel may be data streams such as semblance, signal energy or coherent energy data streams. Such data streams are useful for the study of the resonance response of the voxel to the changes in the stress field. Alternatively, a studyvolume may be associated with a specified time ^^^ ൌ ^^^ ^ ^^^^ ൈ ^^ (where ^^^ is the initialtime of the study volume, δ is the trace data rate and N is the stack size) and its voxel data contains of a single stacked value S(D,k) of a N×δ-second stack for selected data streams D(i) associated with the study volume such as the semblance and signal energy and coherent energy data streams.

[0065] The term "Static Study Volume" refers to a study volume whose voxel data contain of a single stacked value S(D,k) of a N×δ-second stack for selected data streams D(i) associated with the study volume such as the semblance, signal energy and coherent energy data streams. The static study volume has an associated time interval of length N×δ, and astarting time of ^^^ ൌ ^^^ ^ ^^^^ ൈ ^^. Such static study volumes are used to map thepermeability field at ^^^. The evolution of the permeability field in response to changes in the stress field can be determined by analyzing the permeability fields of a series of consecutive static study volumes.

[0066] A "Threshold Condition" for a voxel is a user-defined assertion about or condition on the voxel's data that is either true or false of the voxel's data. For example, a threshold condition for a voxel's semblance S and signal energy E values is any user-defined condition, Con(S,E), which has the property that if Con(S,E) is true and S1≥S and E1 ≥E then Con(S1,E1) is true. For example, the user may specify minimum semblance and signalenergy values ^^^^^ and ^^^^^ and define C(S,E) to be true if and only if ^^ ^ ^^^^^ and ^^ ^^^^^^. As another example, if ^^^ா^^^,^^^ is a coherent energy function, then we can define the threshold condition (called a "Coherent Energy Threshold Condition") ^^^^^^^ா^^^,^^^ that istrue if and only if ^^ ^ ^^^^^ and ^^^ா^^^,^^^ ^ ^^^^^^^, where ^^^^^^^ is a user-specifiedminimum coherent energy value. A threshold condition may further stipulate that the stacking method statistic satisfy a condition such as the condition that the statistic is greater than a user-specified value. A threshold condition may be applied to data values of the voxel of a static study volume (such as the semblance and signal energy) or it may be appliedLVM Ref.340101: 76-24 WO dynamically to the consecutive values of a voxels data streams, such as the semblance and signal energy data stream values. A threshold condition may include other data associated with the voxel, such as the lithology of the rock, the porosity of the rock, the temperature of the rock, etc.

[0067] The term "Active Voxel Threshold Condition" refers to a user-defined threshold condition, which may be a coherent energy threshold condition, that a static study volume's voxel's data must satisfy in order for the voxel to be designated as an active voxel of the study volume.

[0068] The term "Active Voxel" refers to a voxel of a static study volume whose data satisfies a user-defined active voxel threshold condition. For example, the user may examine the range and distribution of semblance and coherent energy values within the entire static study volume and choose a minimum semblance value ^^^in the range 0.45 to 5.5, as representing a measure of unacceptable low coherence, and a coherent energy percentage value ^^^^^^^in the range 5 to 10 percent, representing a lower bound on acceptable coherent energy percentages. The user-defined active voxel threshold condition would then be that an active voxel's semblance value must be greater than ^^^and its coherent energy percentage value must be greater than ^^^^^^^.

[0069] The term "Full Activity Volume" (FAV), sometimes referred to as an "Energy Volume", is a sub-volume of a static study volume comprising the active voxels of the study volume. From this, a permeability field map of the study volume may be obtained. In general, we assume that the voxel's signal energy and coherent energy as well as semblance has been calculated and associated with each voxel in the FAV. A sub-volume of an FAV may sometimes be referred to as an "Energy Sub-volume".

[0070] The term "Permeability Field Imaging" (PFI) refers to the ambient seismic method of mapping the permeability field in its quantitative manifestation and temporal evolution.

[0071] The terms "SET Imaging" and "Tomographic Fracture Imaging" (TFI) refers to the application of 3D imaging technologies - such as color contouring, chair-cuts in a 3D color contoured volume, isosurface extraction, skeletonization, and other feature extraction methods - to a FAV of data produced by analysis of SET data gathered from a study volume.LVM Ref.340101: 76-24 WO

[0072] The term "High Activity Voxel Threshold Condition" refers to a more stringent user-defined threshold condition (a higher minimum semblance value and / or a higher minimum coherent energy value and / or a tighter distribution statistic value, for example) that an active voxel's data values must satisfy beyond the constraints of the active voxel threshold condition. This is also referred to as a “user-defined high activity voxel threshold.”

[0073] The term "High Activity Permeability Field" (HaPF) refers to an energy sub- volume of the FAV that is obtained by identifying all voxels whose data satisfies a user- defined high activity voxel threshold.

[0074] The term "Near Well Active Voxel Threshold" condition or "NWA Voxel Threshold" condition refers to a user-defined threshold condition that an active voxel's semblance and signal energy values must satisfy in addition to the active voxel threshold condition.

[0075] The term "Near Well Active Voxel" or "NWA voxel" refers to an active voxel whose data values satisfy a user-defined NWA Voxel threshold condition. Additionally, NWA voxels must either be in direct contact with a well bore or a proposed well bore location or indirectly in contact with a well bore or proposed well bore location through a chain of connected NWA voxels.

[0076] The term "Enhanced Peak Picker Tool" refers to a method employing coherent energy calculation that operates on the FAV to find local areas of connected high activity voxels that form connected ridges and / or ellipsoids. In three dimensions the ridges and ellipsoids form clouds of high activity permeability field (HaPF) emissions.

[0077] The term "Synthetic Trace Ensemble System" refers to a method or program that can create ensembles of synthetic traces with a specified percentages of relatively coherent traces. The trace ensemble plays the role of a voxel's trace ensemble. Each trace ensemble is referred to as a "Study" of the synthetic trace ensemble system. The synthetic trace system specifies the number N of traces in an ensemble, the number of samples per trace, a sample data rate, a semblance window, a semblance window shift. Each study further specifies number of coherent traces in its trace ensemble. By computing the semblance, signal energy and coherent energy of each study (where the coherent trace percentage varies from 0 % to 100%) the relationship between semblance, signal energy and coherent energy can be studied. The stack of a study's trace ensemble is referred to as the study's "Aperture Stack Trace".LVM Ref.340101: 76-24 WO

[0078] “High fluid recovery” refers to the method provided herein that optimizes fluid recovery by positioning a well to maximize the number of near well activity (NWA) voxels. The fluid may be a liquid, a gas, or a combination of a liquid and gas.

[0079] A “User-selected Statistic” refers to the statistical parameter associated with a stacking method (the "Stacking Statistic") used in stacking the semblance, signal energy and coherent energy values of voxels of a study volume. Preferably, the stacking statistic is a measure of the variation or distribution of the population of values, such as a standard deviation or a standard error of the mean. The term "User-defined Stacking Statistic Value" or "USS" value refers to a user-defined value of the stacking statistic for semblance, signal energy or for coherent energy. They are used in the specification of the high activity voxel threshold condition for the study volume. In an embodiment, the USS value might be equivalent to one-standard deviation or greater. A "Characteristic Semblance Value" is a semblance value for which the corresponding stacking statistic is equal to the semblance's USS value. Similarly, a "Characteristic Energy (or Coherent Energy) Value" is an energy value for which the corresponding stacking statistic is equal to the signal energy's (or coherent energy's) USS value. For example, the stacking statistic of a voxel data value such as a standard deviation or a standard error of the mean, may be required to be greater than or equal to the corresponding characteristic value. Depending on the application of interest, the USS values may be a lower or higher value. For example, for high resolution data (e.g., voxels having smaller volumes), the USS values may be relatively high, such as greater than or equal to two standard deviations, in effect decreasing the tolerance of the high activity threshold condition and, in effect, decreasing the total number of HaPF voxels. In general, identifying voxels that meet more stringent activity threshold conditions can provide more precise borehole locations for optimized or high fluid production compared to a well borehole located away from these voxels. The methods provided herein, of course, are compatible with a range of statistical parameters, so long as the statistical parameter is a measure of the distribution of the voxel data stream values.

[0080] Further description of SET can be found in US Patent No.7,127,353 and WO 2020 / 242986. SET is the basis of the imaging technology described herein and thus can be characterized as foundational. Briefly, a SET array is established so as to acquire seismic energy data due to changes in the transient stress field in a study volume. It is a method for the collection of seismic signals from sub-surface sources to provide information about theLVM Ref.340101: 76-24 WO study volume. We then manipulate these data using various analysis methods to determine properties such as semblance, signal energy and coherent energy.

[0081] The physical property, energy, is inter-derivable with various energy-related, physical properties such as power and work. Consequently, although the methods, systems and procedures provided herein may use the physical property term "energy", the term energy may be replaced with any inter-derivable, energy-related physical property. This reflects that the invention is compatible with any inter-derivable, energy-related property, including, but not limited to power and work.

[0082] A fluid reservoir refers to a geologic formation containing one or more fluids embedded or trapped within the formation. Accordingly, a fluid reservoir is one example of a study volume, particularly for applications related to fluid recovery. Fluid reservoirs may have naturally occurring permeability and porosity. Fluid reservoirs may contain hydrocarbons or molecules comprising primarily hydrogen and carbon, but may contain other elements, for example, oxygen, nitrogen, and sulfur. Hydrocarbons may refer to fluids targeted for recovery and production common in the oil and gas industry, including oil, natural gas, condensate and the like, but also include more complex molecules, such as naturally occurring polymers and paraffins. Other fluids include, but are not limited to hydrothermal fluids, water, helium and the like.

[0083] The science underlying the concepts and technologies presented herein is extensively covered in Permeability field imaging: Mapping the geocritical crust’s permeability field, (Geiser et al. AAPG Bulletin 107(9): 1581-1608 (Sept.2023)) which is specifically incorporated by reference herein. US Pat. No.7,127,353 (Geiser) discusses SET. In US Pat. No.7,127,353 the SET data are used to determine semblance. The instant technology, in contrast, uses the data to compute a fundamentally different property, namely, the signal energy and the coherent energy of a study volume's voxel's trace ensemble associated with the emitted seismic signal from the voxel. Provided herein are methods and systems that use the data provided by SET to calculate signal energy, coherent energy and semblance over the study volume.

[0084] Provided herein is the use of semblance, signal energy and coherent energy of a voxel to determine the permeability field. The difference between semblance and signal energy is reflected in FIGs.4A and 4B. In FIG.4B (semblance plot), note that at the rightLVM Ref.340101: 76-24 WO side of the yellow box, there are 4 prominent elongate red (high semblance value) blobs in the white circle with values similar to those displayed at the left end of the box, the region of the mine blast response. In FIG.4A (signal energy plot) the same time frequency location is shown by the yellow circle in the yellow box. The same 4 blobs are found but have values indicating that the signal energy, a physical measure, has a significantly lower value than the signal energy displayed in the blast region in the left side of the yellow box. The semblance and signal energy plots in FIG.7 also demonstrate the difference between semblance and signal energy as proxies for energy emission from the voxel rock. The examples in FIG.7 demonstrate that semblance alone is not able to properly track changes in the amplitude of signal energy emissions. FIG.7 also demonstrates that signal energy alone is not sufficient as an energy proxy - rather it must be combined with semblance to distinguish coherent energy from incoherent energy. We know that there is a positive correlation between the energy emitted by the voxel rock material and its fluid content, thus demonstrating that a coherent energy computation for the voxel can be used as a more accurate measure of the permeability field than the semblance values alone. While semblance plots have been used for mapping permeability fields, use of a physical property measure such as coherent energy can provide improved permeability field maps with improved permeability field architecture, with attendant increase in reliability for applications thereof, including fluid recovery from a reservoir field. This mapping makes use of the seismic energy generated by country rock itself in response to the continual energy flux of an ambient stress field generated by a transient seismic energy passing through the country rock within the study volume.

[0085] Example 1: Development of Permeability Field Imaging

[0086] This example presents the historical development of permeability field imaging. The term "energy" is used in this example in its direct physical sense, namely energy emission from the rock fabric within a study volume. All other examples (Examples 2 - 10) distinguish between the concepts of the energy emitted from a voxel's rock fabric, "signal energy" of a voxel, and "coherent energy" of a voxel, the latter two being values calculated from a voxel's trace ensemble..

[0087] Research over the past several decades has shown that a fundamental feature of the Earth’s brittle crust is its critical state (Bak 1996, Leary 1997). One of the manifestations of this state is the crust’s weak nature. Originally, this was thought to be due to failure on pre- existing fractures at a deviatoric stress of less than 0.01 bar (Ziv and Rubin, 2002). MoreLVM Ref.340101: 76-24 WO recent work (Malin et al, 2020, Sicking and Malin 2019, Geiser et al 2023) indicates that while this assessment of crustal strength is accurate, much of the energy emitted is the result of resonance associated with fluid-filled voids and the elastic response of crystal lattices, rather than fracture propagation alone.

[0088] In the late 1970s and early 1980s, as part of the Nuclear Test Ban Treaty (NTBT), Soviet and American scientists developed Seismic Emission Tomography (SET) to detect impulsive events anywhere in the Earth’s brittle crust. SET differs from reflection seismology where the signal source is at the surface and its magnitude and timing is controlled by seismic crew. In contrast, with SET the signal source is within the study volume itself, i.e. the rock itself, and is controlled by natural processes. NTBT seismic networks were then considered as a useful tool for imaging the weak seismicity that, while known to exist and dominate the seismic spectrum, was not detectable with standard seismological methods.

[0089] The significance of evidence indicating that the Earth’s crust exists in a critical state (Bak 1996, Leary 1997) and the potential of SET for imaging this activity was recognized. This concept was tested by a sparse network of 8 micro-arrays spread over a region of approximately 50 × 50 km, where each micro-array consisted of three 1C geophones in an isosceles array about a central 3C phone. Using continuous recording at around 500 Hz, over a period of 8 hours with data “stacked” to form eight successive 1-hour volumes comprising 3D “pixels” (i.e., voxels or cubes) with edges approximately 100 m in size, successful imaging dislocation “creep” at a depth of 20 km associated with the motion of a tear-bounded thrust was successful.

[0090] FIG.1 illustrates the first use of SET to image crustal activity. Specifically, FIG. 1 shows successive time / space maps showing dislocation creep on a tear bounded thrust at a depth of 20 km. Hour 2 (left panel) shows activity on tear fault boundary while beginning to move laterally onto the flat. Hour 4 (right panel) shows activity largely restricted to the flat. The map size is about 44ൈ44 km with a map grid size of 8ൈ8 km. Voxel edge dimension was 250 m.

[0091] One of the most important and unique attributes of SET is that it maps energy emission in 5 dimensions: Space (x,y,z), Energy and Time. An example of this can be seen in FIG.1. Temporal mapping is possible due to both continuous recording and high sample rates (≥ 500 Hz). Thus, near real-time displays of energy behavior on the order of 1 second orLVM Ref.340101: 76-24 WO more are attainable through SET technology. In the remainder of this example, we refer to SET imaging as 5D.

[0092] A novel computer program utilizing background seismicity to image faults was developed (Geiser and Seeber 2008). Heffer et al. (1995) investigated Rate Correlation statistics as applied to producing hydrocarbon field. Among their observations was evidence that with respect to injector wells, producing well lying within a 90° sector of arc bisected by maximum horizontal stress (SHmax), would respond within no more than a day at distances of at least 5 km.

[0093] This finding conflicted with the existing permeability field models, which assumed an essentially isotopic homogenous medium. It was, however, consistent with the growing evidence for the log-normal distribution of fracture size / frequency, indicating that the permeability field was highly heterogeneous. Log-normal distribution of fractures in turn implied that the permeability field was probably dominated by a relatively small number of large fractures with high permeability by which pressure communication over distances of kilometers was possible.

[0094] By the mid-1990s it was known that the crustal failure would occur under deviatoric stress values of < 2 bars, and was probably much weaker. In 2000, Ziv and Rubin showed that deviatoric stress of less than 0.02 bar were sufficient to cause failure on preexisting fractures. Recognizing that fluid pressures associated with production and injection were far in excess of these values, it was reasoned that it might be expected the normal well operations would induce seismicity, permitting mapping of the permeability field. An immediate challenge to testing this assertion was due to the log-normal distribution of fracture size / frequency and, consequently, most of the activity would be events well below resolution limits.

[0095] It is now known that relatively high permeability fracture zone surfaces of the High Activity Clouds of the HAC (Geiser et al, 2023) and dislocation creep associated with fault motion, including as shown in FIG.1. The validity of the SET imaging technology led to the development of the initial SET imaging technology focusing on the permeability field with improvements commercialized under the moniker Tomographic Fracture Imaging (TFI).LVM Ref.340101: 76-24 WO

[0096] The ongoing research and development using SET data is a basis of the instant technology of crustal resonance and the ability to map the permeability field in terms of energy rather than semblance.

[0097] The more than 20 years of development, discovery and research shows that SET technology and its ability to improve our understanding of crustal and deep earth tectonics is akin to how radio telescopes enhanced our understanding of the astronomical universe. Thus, SET opens a new window of opportunity, and a paradigm shift, in how the Earth’s crust can be studied. The result facilitates a new, previously unavailable view into the behavior of both the brittle crust and the “Deep Earth.” In particular, the unprecedented discovery of the episodic periodicity of the frequencies of energy resonance of the brittle crust.

[0098] Example 2: The methods for determining the frequency spectrum of a discrete time signal S include Fourier Analysis, Spectrograms, and Wavelet Analysis.

[0099] Fourier analysis calculates the spectrum of frequencies of S over a fixed time window by, for example, effectively convolving S with sinusoidal curves of varying frequencies. This does not, however, provide the dynamics of the frequency spectrum over time.

[0100] A spectrogram of S provides a dynamical view of the frequency spectrum over time by computing the Fourier frequency spectrum over a moving fixed length time window. This approach yields the most accurate frequency resolution compared to wavelet analysis but at a sacrifice of time resolution.

[0101] Wavelet analysis of S provides a dynamical view of the frequency spectrum over time by convolving S with a variable length, variable frequency wavelet through time. This approach yields the most accurate time resolution at some sacrifice to frequency resolution.

[0102] FIG.2 is a spectrogram of a stacked focus trace of a Colombia earthquake showing resonance (depth 1900 m; aperture 2000 m – 904 traces).

[0103] FIG.3 illustrates a wavelet analysis of a signal data stream ^^^^^^. The mother wavelet is shown as function ^^^1^ with a frequency of 5 Hz and a time window of 1 second. Stretching the mother wavelet by a scaling factor of 2 changes its corresponding frequency, resulting in scaled wavelet ^^^2^ with a frequency of 2.5 Hz and a time window of 2 seconds.LVM Ref.340101: 76-24 WO The wavelet can be convoluted with the data stream ^^^^^^ over the wavelet time windowcentered around ^^. A "Wavelet Coefficient", ^^^^^^^, ^^^, for scale ^^ and time ^^ is defined as(EQ 4) ^^^^^^^, ^^^ ൌ ^^^^^^ ⊗ ^^ ൌ ∑௧ା^^^^ / ଶ௧ି^^^^ / ଶ ^^^^^, ^^^ ൈD(t),t and ^^^^^^ is equal to the sizeof the time window of ^^^^^^. The wavelet coefficients can be color contoured generating a display of the temporal dynamics of the data stream's frequency spectrum over time as in FIGs.4A-4C.

[0104] FIG.4A illustrates the wavelet analysis of the signal energy of a voxel's stacked focused trace, including a blast interval (approximately 20 sec.) and a subsequent resonance period. FIG.4B illustrates the wavelet analysis of the semblance of the same voxel's trace ensemble. FIG.4C illustrates a zoomed in view of the wavelet analysis of FIG.4A comparing the 20 second blast interval with the 30 seconds of resonance immediately following. In particular, note that the semblance display does not distinguish between the blast period and the subsequent resonance period where as the signal energy display does so.

[0105] Example 3: The equations for a voxel's semblance and signal energy and their relationship and properties.

[0106] Define ^^^^^^^^ to be the stack of the focused traces within the aperture of the voxel. ^^^^^^^^ is called the "Aperture Stack trace" or simply "Aperture Stack" and is defined as: (EQ 5) ^^^^^^^^ ൌ: ∑௫ୀே^௫ୀ^ ^^௫^^^^of the ^^௧^trace. ^^௧is the number of traces in the voxel's aperture and ^^ is a time index.

[0107] The power of the aperture stack trace, treated as a signal, is defined as (EQ 6) ^^^^^^^^^^ ൌ: ^ ∑^ୀ^ൈ^^ାேೞି^ ^^^^^^ ^ ଶ^ୀ^ൈ^^ ^^ ^ ,semblance time window, ^^ℎ is the semblance window shift, and ^^ is a time index with values 0,1,2,⋯. The data rate of ^^^^^^^^^^is ^^ ൈ ^^ℎ. Since energy is defined as the time x power, the energy of the aperture stack traceover the time interval ^^ ൌ ^^ ൈ ^^^ is obtained from the power of the aperture stack butmultiplying ^^^^^^^^^^ by ^^.LVM Ref.340101: 76-24 WO

[0108] Without precluding other definitions of energy of the voxel's ensemble, herein we shall use the term voxel's signal energy to refer to energy computed by the energy equation: (EQ 7) ^^^^^^ ൌ:∑^ୀ^ൈ^^ାேೞି^ ^^^^^^^^^^ଶ^ୀ^ൈ^^ .of semblance, herein we shall use the termrefer to semblance computed by the standard semblance equation (Neidell and Taner, 1971) expressed as the normalized signal energy: (EQ 8) ^^^^^^ ൌ: ா^^^ே^^^ , where the signal energy normalizer is (EQ 9) ∑^ୀ^ൈ^^ାேೞି^^∑௫ୀே^௧ ^^^ ^ ଶ^ୀ^ൈ^^௫ୀ^௫ i^^ ^from voxel to voxel and evenfrom use of ^^௧as a factor in the signal energy normalizer is required to guarantee that semblance values lie within the unit interval ^0.0,1.0^ and to provide, as much as possible, uniform and comparable semblance values from voxel to voxel and geophone field to geophone field. A semblance of 1.0 means total coherence (all traces are equal) and low semblance values means low coherence.

[0111] A significant property of semblance is that it is scale-invariant in the sense that ifthe amplitudes of the aperture traces are uniformly scaled by a factor ^^ ^ 0, the semblancevalue remains unchanged. This makes it problematic as a proxy for energy emission. For example, if the amplitudes of the voxel aperture traces are doubled, the signal energy will quadruple but the semblance will remain unchanged.

[0112] To see this, define the scaled aperture traces ^^^௫^^^^ ൌ ^^ ൈ ^^௫^^^^. We shall showthat the semblance, ^^^^^^^, of the scaled aperture traces ^^௫^is equal to the semblance ^^^^^^ofthe (unscaled) aperture traces ^^௫. The semblance equation for the scaled aperture traces is (EQ 10) ^^ா ^^ ^^^^^ ൌ ೞ^ ேೞ^^^where ^^ ^ୀ^ൈ^^ାேೞି^௫ୀே^ ^ଶ^ୀ^ൈ^^ାேೞି^௫ୀே^^^^^ ൌ ∑ ^ୀ^ൈ^^ ^∑ ௫ୀ^ ^^௫^i^൧and ^^^^^^^ ൌ ^^௧ ∑ ^ୀ^ൈ^^ ^∑௫ୀ^^^^^௫^^i^^ଶ^ .Note that ∑ ௫ୀ^ ௫ ൌ ∑ ௫ୀ^ ^^ ൈ ^^௫^^^^ ൌ ^^ ൈ ∑ ௫ୀ^ ^^௫^^^^, and therefore the scaled signal energyLVM Ref.340101: 76-24 WO (EQ 11) ^^^^^^^ ൌ ^^ଶ ∑^ୀ^ൈ^^ାேೞି^ ∑௫ୀே^ଶଶ^ୀ^ൈ^^ ^ ௫ୀ^ ^^௫^i^൧ൌ s ൈ ^^^^^^ .Next, note that ∑௫ୀே^ ^ ଶ௫ୀ^ ^^^௫^i^^ ^ ൌ ∑௫ୀே^ ଶ ଶ ∑௫ୀே^ ଶ௫ୀ^ ^s ൈ ^^௫^i^^ ^ ൌ s ൈ ௫ୀ^ ^^^௫^i^^ ^and therefore the scaled ^^ ^^^^

[0113] ^^ ^^^^ ൌ ^^ ൈ sଶ ൈ ∑^ୀ^ൈ^^ାேೞି^ ^∑௫ୀே^^ ^^^ ^i^^ଶ^ ൌ sଶ௧ ^ୀ^ൈ^^ ௫ୀ^ ௫ ൈ ^^^^^^ .^,establishing the invariance of semblance under uniform scaling of the aperture trace amplitudes.

[0114] Scale invariance of semblance is one of the main reasons that semblance by itselfis not preferred as an energy proxy. On the other hand, in EQ 11, ^^^^^^^ is equal to ^^ଶ ൈ ^^^^^^and is the voxel signal energy of the scaled aperture traces. It follows that, while semblance is scale invariant, the signal energy of the scaled aperture trace is ^^ଶtimes the signal energy of the (unscaled) aperture traces.

[0115] Example 4: Problems with semblance as a proxy for energy emitted from a voxel

[0116] Semblance has the property that if the traces are identical (i.e. maximum coherence) then the semblance is 1, independent of the amplitude of the traces. Also, equation EQ 14 above shows that semblance is scale invariant. Therefore, semblance mathematically does not distinguish between high amplitude – high coherence and low amplitude – high coherence. Field studies have shown that high activity around a well bore during stimulation is associated with correspondingly high semblance values in the near well voxels. It has also been used as a means for identifying zones of seismic radiation [Tchebotareva, et al 2000]. While it may show that seismic emissions are occurring, it does not provide is a measure of the energy of those emissions. Wavelet analysis of signal energy and semblance of data gathered from a geophone field in during mine-blast activity is illustrated in FIGs.4A-4B and FIGs.5A-7C. They demonstrate that signal energy provides a more emphatic presentation of the pre-blast environment, the blast, as well as the subsequent period of resonance (FIG.4C). In the next two examples, Example 5 and Example 6,LVM Ref.340101: 76-24 WO synthetic trace modeling is used to study the relationship between semblance and signal energy in more detail as well as the relationship between semblance, signal energy and the coherent energy of the voxel's trace ensemble.

[0117] Example 5: Synthetic Trace Modeling Demonstrating the Relationship Between Semblance and Signal Energy

[0118] In this example, we compare semblance with signal energy to show that semblance may be used to provide quality control over the signal energy of voxel's stacked aperture trace.

[0119] To study the relationship between the semblance and signal energy of the aperture traces, we generate synthetic traces with six temporal segments illustrating various trace behaviors, including fixed and / or varying frequencies, different levels of noise, a frequency "burp" and a data burst, the latter to simulate a high-amplitude event occurrence. The frequency components during the frequency variation period can be set to vary (or not) between traces. Additionally, to each trace is added a parallel random noise trace that include a noise burst as indicated in FIG.6.

[0120] The results of this type of modeling demonstrates that semblance and signal energy are not preferred on their own as a proxy for energy emission from a voxel. The results also show that they can be used together to provide a more reasonable and more accurate indication of energy emission than semblance alone.

[0121] FIG.6 shows the architecture of the synthetic trace comprised of two sinusoidal segments, Sinus1 and Sinus2, each comprising a sum of cosine functions with separate amplitudes and frequencies, and a Noise segment (randomly generated). Added to and in parallel with the trace is a noise trace (which includes Noise Burst segment), and a Data Burst segment as indicated. The Frequency Variation section in Sinus 2 permits changing the amplitudes and frequencies of the Sinus2 sinusoidal components providing a high level of decoherence.

[0122] FIG.7 displays the wavelet analysis of the signal energy and semblance computed from the same synthetic dataset. Each display shows the wavelet coefficients of the wavelet analysis (upper portion) and the actual data (lower data bar). In the semblance display, the Sinus 1 segment and the portions of Sinus2 that are not altered by the noise burstLVM Ref.340101: 76-24 WO or data burst, track the frequency exhibited in the signal energy display. But the amplitudes of the semblance data do not track the amplitudes of the signal energy data, demonstrating that semblance cannot be a proxy for the amplitude variation of the energy emitted from the voxel rock.

[0123] Most conspicuous are the differences in the frequency variation segment and data burst segment between the two displays. In the frequency variation segment, the semblance data shows strong decoherence but the signal energy data for that segment is around the average signal energy value. Using this information from the semblance data, one can mark the signal energy emission during this segment as unreliable and the coherent energy as low. On the other hand, during the data burst segment, there is a strong increase shown in the signal energy data but the amplitude of the semblance data does not differentiate this segment from the values directly before and after the data burst segment. Nevertheless, by having a value close to 1.0, it signals that the signal energy data is to be relied on (i.e. close to the coherent energy) during the data burst segment.

[0124] FIG.7 demonstrates how neither semblance nor signal energy alone properly identify the variation in energy emission from the voxel. At the same time, FIG.7 demonstrates how semblance can be used to provide quality control over the signal energy of the aperture trace.

[0125] Example 6: Synthetic trace modeling demonstrating the relationship between semblance, signal energy and coherent energy

[0126] The term coherent energy of a voxel refers to the energy value of the coherent traces of the voxel's trace ensemble, calculated over the semblance time window. One can expect that the quality of each trace in the trace ensemble will vary depending on such things as the accuracy of the velocity model; any ”noise” imposed on the signal from sources along the pathway; the attenuation of the seismic signal along different trace pathway through the velocity model. With respect to the attenuation issue, note that if signal ^^1 is an attenuationof signal ^^2 (in the simple form of ^^1^^^^ ൌ ^^ ൈ ^^2^^^^ for a constant ^^ ^ 1) then it can beshown that semblance of S1 and S2 is < 1; that is, attenuation decreases semblance. For this reason, it is important to correct for attenuation where possible.

[0127] Our hypothesis is that the traces in the aperture trace ensemble with the highest coherence are the most suitable traces from which to extract the energy emitted from theLVM Ref.340101: 76-24 WO voxel – these traces are referred to as the “coherent” traces. While one does not know apriori which traces are coherent and which are not, the relationship between semblance, signal energy and coherent energy can be studied by creating a "Synthetic Trace System", comprising a method or program that creates of ensembles of synthetic traces with a specified percentages of relatively coherent traces. The synthetic trace system generates the synthetic trace ensembles (each ensemble of which is referred to as a "Study") in which we can control the percentage of coherent traces. Coherent traces are designed to have high coherence, and “no-coherent” traces are designed to have variously low coherence. Each study in the synthetic trace system used in Example 6 has an ensemble of 500 traces, each trace has 100,000 samples with a data rate is 4ms. The semblance window size and shift are 200 ms and 100 ms respectively. For each study, the semblance, signal energy, and coherent energy (energy of the coherent traces) are computed. By sequentially varying the percentage of coherent traces in each study, the relationships between semblance, signal energy, and coherent energy can be analyzed

[0128] As expected, higher percentages of coherent traces correspond to higher semblance values and, by definition, the maximum semblance value of 1.0 corresponds to total coherence of the traces in the voxel's trace ensemble. Additionally, the studies show that there is a quadratic relationship between the ensemble's semblance and coherent energy (FIG.8) and a quadratic relationship between the ensemble's signal energy and coherent energy (FIG.9). In contrast, the relationship between the semblance and the signal energy is linear (FIG.10A). Define the "Coherent Energy Percentage" function, ^^^ா^^^^^ ൌ ^^^ ⁄ ^^,where ^^ is the signal energy and ^^^is the coherent energy. Consistent with the above relations between semblance, signal energy, and coherent energy, the coherent energy percentage also has a quadratic relationship to semblance. FIG.10B is an example the quadratic relationship between the coherent energy percentage and semblance. ^^^ா^^^^^ denotes user-defined coherent energy percentage used to estimate ^^^ா^^^^^.

[0129] The "Default Coherent Energy Percentage" function is defined as ^^^ா^^^^^ ൌ ^^^^^^^^^^^^^ଶ ^ ^^ െ ^^, 0, 1) where ^^ is user-specified value in the range^0.5,1.0^ and ^^^^^^^^^^^^^, 0,1^ ൌ ^^^^^^^0,^^^^^^^1, ^^^^.LVM Ref.340101: 76-24 WO For example, Synthetic Trace Management System studies suggest choosing C = 0.86 toprovide the least average value of the relative difference ^^^^^^ ൌ |^^ ൈ ^^^ா^^^^^ െ ^^^| / ^^^^௫where ^^^^௫is the maximum signal energy.

[0130] As another example of a user- defined coherent energy percentage function one may define ^^^ா^^^^^ to be the general quadratic equation: ^^ ^^^^ ൌ ^^ ൈ ^^ଶ^ா^ ^ ^^ ൈ ^^ ^ ^^,where ^^, ^^, and ^^ are specified by the user. For example, let ^^^denote a user-specified semblance value between 1.0 and ^^^, where ^^^is the user- active voxel semblancethreshold value. Let ^^^and ^^^be user-specified coherent percentages (of the signal energy) corresponding to ^^^and ^^^(see FIG.10C). This yield three equations which suffices to determine the values of ^^, ^^, and ^^: (1) ^^^ா^^1.0^ ൌ 1.0;(2) ^^ ^^^^^ ^^^Since that S, and the graph of ^^ ^^^^ is concave up^ா^slope), the function ^^ ^^^^ and the user-specified values ^^ , ^^ , ^^ , and ^^ , must further^ா^ ^ ^ ^ ^satisfy the conditions that:(4) ^^ ^^^^ ^ ^^;^ா^^^ െ ^^^ ^If the active voxel's semblance threshold value ^^ is chosen under the assumption that the^coherent portion of the corresponding signal energy is effectively zero, then the above ⁄condition (3) simplifies to ^^ ^^^ ^ ൌ 0. If ^^ is chosen to be ^1 ^ ^^ ^ 2 , then the only user^ா^ ^ ^ ^assigned values are active voxel's semblance threshold value ^^ and coherent energy^percentage parameter ^^ corresponding to ^^ . The data from the studies as shown in FIGs. (8,^ ^9, 10A, 10B), suggest that ^^ ^^^ ^ ൌ 0 a reasonable working hypothesis to^when defining the coherent energy percentage function. We refer to these conditions (1) - (5) as the "Quadratic Coherent Energy Percentage Function Conditions".LVM Ref.340101: 76-24 WO The definitions of the Default Coherent Energy Percentage function and the Quadratic Coherent Energy Percentage Function Conditions are meant as examples and not as a restriction of other possible definitions of the coherent energy percentage function.

[0131] Use of these relationships are an example of an instant method to calculate the coherent energy portion of the signal energy used for permeability field mapping. For example, for a given study volume, a user may specify the coherent energy percentage function, ^^^ா^^^^^. Define the "Coherent Energy Function" ^^^ா^^^,^^^, whose value is the coherent energy portion of the signal energy E given semblance ^^ and signal energy ^^. By definition of the coherent energy percentage function, ^^^ா^^^^^, the coherent energy function ^^^ா^^^,^^^ satisfies equation EQ 15: (EQ 14) ^^^ா^^^,^^^ ൌ ^^^ா^^^^^ ൈ ^^.

[0132] Example 7: Voxel signal energy and resonance in the ambient stress field.

[0133] Both signal energy and semblance can also be used to examine energy emission from a single voxel. Both are proxies for energy emission from the voxel rock but in significantly different ways: they both are attributes of the seismic energy emitted from a voxel but the energy attribute is a more direct proxy because it is a measure of the energy of the stacked focused trace of the voxel while semblance is unable to reliably distinguish variations in the amplitude of the emitted seismic energy. Semblance does provide quality control in that it reveals the degree of coherence of the traces in the voxel's trace ensemble. By examining the frequency variation in the coherent energy (or signal energy) of a voxel, resonance phenomena in the ambient stress field are illuminated. To demonstrate this, aperture trace data of a voxel at a depth of 4200 feet was collected during mine blast activity from a geophone array in an RGP gas field in southeastern Illinois (FIG.11).

[0134] The geophone data referenced in FIG.11 was collected over a 24 hour period. Voxel signal energy and semblance were calculated over a period of time that included a mine blast from one of the active mines.

[0135] As shown in FIGs.4A, 4C, the mine blast event started at about 17:23:37 and continued for about 21 seconds followed be a period of about 30 seconds of resonance. The use of the aperture signal energy makes the mine blast event and resonance stand out. Analysis of signal energy and coherent energy provide a means to characterize the resonanceLVM Ref.340101: 76-24 WO response of the voxel's rock fabric generated by the physical properties of rock and its fracture network in response to the changes in the ambient stress field.

[0136] Example 8: Application of 3D color contouring, isosurface extraction and skeletonization methods to delineate the permeability field.

[0137] The 3D color contouring, isosurface extraction and skeletonization examples discussed herein are applied to the semblance values of a Full Activity Volume (FAV). This demonstrates how uses of these mapping techniques can be applied with the instant methods, including by applying these techniques to the voxel coherent energy values in the FAV. The following four embodiments (i)-(iv) demonstrate the 3D color contouring, isosurface and skeletonization methodology.

[0138] (i) Referring to the chaircut, color-contoured FAV in FIG.16, the lower semblance gradients are interpreted to represent volumes of higher permeability (k) (hot colors) and higher semblance gradients lower k (cool colors). (ii) In FIG.13, the term " HaPF surfaces" refers to zones of high semblance values in the FAV. The HaPF surfaces consist of high local-semblance voxels that connect to form sub-volumes of the FAV. These sub- volumes typically appear as clouds of high ambient seismic activity. These clouds contain connected ridges of high semblance values. (iii) The term "Permeability Field Imaging" or "PFI" is a signal processing method to extract these HaPF surfaces ridges through skeletonization (see FIG.12). Successive isosurface extraction (FIG.19) in the Barnett Shale unpacks the complexity of the permeability field. (iv) The permeability field mapped with PFI is a product of the complete spectrum of the power law fracture population and spatial frequency distributions. Malin et al, (2020) show that because of this, there can be no representative elementary volume, meaning that no spatially limited “rubber stamp” exists that can be repeated to model the entire reservoir. The permeability architecture cannot be deduced from core samples and reservoir modeling, it must be mapped directly at all scales, which PFI does down to the 8 meter scale. A sequence of iso-surfaces and the volumes they surround, extracted from the Barnett FAV (FIG.19) is an example of the spatial complexity of the permeability field’s architecture.

[0139] Example 9: Permeability mapping using semblanceLVM Ref.340101: 76-24 WO

[0140] In the following examples using previous field work, the permeability field was mapped using semblance. The same methods and techniques can use coherent energy to achieve a more accurate mapping.

[0141] FIG.12 is a chair cut of a 3D full activity volume (FAV), with the image labelled to show areas of low activity permeability field (LaPF) and areas of high activity permeability field (HaPF). In FIG.13, solid lines are added, showing the HaPF skeletonized surfaces within the FAV. It should be noted that the HaPF surfaces are embedded in the FAV. It should also be noted that HaPF areas form closed volumes and the LaPF areas fill in the interstitial spaces.

[0142] FIGs.14-15 is a comparison of 4D seismic to SET imaging showing the location of fluids and semblance data. FIG.14 is a 4D seismic image illustrating the location of fluid increase. FIG.15 shows a SET image illustrating the permeability field of the same location, taken using a 30-second stack technique.

[0143] FIG.16 is a chaircut, color-contoured image highlighting areas of higher permeability (k) against areas of lower k over a FAV. Regions of tighter packed isosurfaces correspond to lower permeability (^^) while regions of more loosely packed isosurfaces correspond to higher ^^.

[0144] FIG.17 summarizes a case study of the SET imaging technique and the use of skeletonization of NWA voxels around a well bore during stimulation. The first well intersected and activated a natural fracture network near a second well used for monitoring (“monitoring well”). Included in FIG.17 is a composite of frames from a video showing the progress of the stimulation of the first well. The pumping into the first well results in fracture propagation into the nearby monitoring well.

[0145] FIG.18 shows high semblance valued voxels illuminating a single-stage activation of a natural fracture network during frac.

[0146] FIG.19 By successively increasing the minimum displayed semblance value, the resulting isosurface extraction unpacks the complexity of the permeability field.

[0147] FIG.20 is a visual representation showing that no production operations affect surface groundwater aquifers. The view looks north at the TFIs that map the fracture / faultLVM Ref.340101: 76-24 WO fairways of the permeability field illuminated during the frac of a Devonian tight gas play in southwestern West Virginia. These are part of the natural fracture / fault system and show the extent of this system that was activated by increased fluid pressure during the frac. The layer labeled “interbedded sands / shales” is the reservoir seal. It consists of 0.5m to 1 m thick layers and is thin bedded relative to the reservoir. The reservoir consists of thick bedded (1 – 2 meter) thick layers of siltstones and shales. The difference in bedding thickness and the mechanical anisotropy of the reservoir seal makes a mechanical barrier to fracture propagation, which is why it is a seal. This is also what the TFIs show and why they are stopped at the reservoir seal.

[0148] Exemplary method of mapping a permeability field:

[0149] FIG.21 provides a flow chart summary of an embodiment for mapping a permeability field architecture of a study volume in country rock. In step 100, a study volume in country rock is identified, wherein the study volume comprises a plurality of voxels.

[0150] 110 From that study volume, seismic trace data is acquired from a network of seismic sensors above the study volume.

[0151] 120 As subsequently explained, each voxel of the plurality of voxels has a trace ensemble and an aperture. The seismic traces in the aperture of each voxel in the study volume are focused on the location of the voxel thereby forming the voxel’s trace ensemble comprising focused aperture traces. Of course, each voxel has a known location within the study volume.

[0152] 130 From the steps 100, 110 and 120, value data streams are calculated for each voxel over a series of time intervals, wherein the value data streams comprises signal energy, coherent energy, and semblance values calculated for each voxel trace ensemble for each time interval.

[0153] 140A (optional) From step 130, the value data streams for each voxel can be analyzed for resonance phenomena related to the permeability of the voxel's rock mass.

[0154] 140B From step 130, for each time interval of the series of time intervals, a static study volume (SSV) is determined, comprising the voxels of the study volume together with each voxel's data comprising their geological context, semblance value, signal energy value,LVM Ref.340101: 76-24 WO and coherent energy value and their associated statistics, calculated from each voxel trace ensemble over the static study volume associated time interval. In this context, “associated statistics” refers to a statistical parameter useful for characterizing the computed values, such as standard deviation or standard error of the mean.

[0155] 150A From the above steps, a full activity volume (FAV) is determined by identifying all voxels of the static study volume having a semblance and signal energy and coherent energy values that satisfies a user-defined Active Voxel Threshold condition.

[0156] 150B Optionally, a more stringent user-defined active voxel threshold condition may be applied such as a High Activity Threshold condition forming a permeability field (HaPF) volume or a Near-Well-Activity (NWA) threshold condition forming a volume of NWA voxels.

[0157] 160 From 150A and / or 150B the permeability field is mapped by applying to the created volumes of voxels, surface extraction methods as known in the art, such as isosurface extraction, skeletonization, and 3D color contouring.

[0158] In this manner, the permeability field of the study volume is mapped.

[0159] Such a mapping has a range of important applications. Examples include, but are not limited to, locating regions of high permeability for the development and / or monitoring of an enhanced geothermal system, a CO2sequestration system, or a waste water injection site; locating proposed well bores for optimized fluid production; and monitoring the response to well bore stimulation and production.

[0160] References

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[0162] Engelder, T., J. Vermilye, A. Lacazette, P. A. Geiser, C. Sicking, and J. N. Hooker, 2022, Seismic emissions reveal the mechanical stratigraphy of the Middle Paleozoic section under the Appalachian Plateau, Pennsylvania, in C. Koeberl, P. Claeys, and A. Montanari, eds., From the Guajira Desert to the Apennines, and from Mediterranean microplates to the Mexican killer asteroid: Honoring the career of Walter Alvarez:LVM Ref.340101: 76-24 WO Washington, DC, Geological Society of America Special Paper 557, p.239–266, doi:10.1130 / 2022.2557(14).

[0163] Geiser, P. A., and T. J. Engelder, 1983, The distribution of layer parallel shortening fabrics in the Appalachian foreland of New York and Pennsylvania: Evidence for two non-coaxial phases of the Alleghenian orogeny, in R. Hatcher, H. Williams, and I. Zeitz, eds., Contributions to the tectonics and geophysics of mountain ranges: Washington, DC, Geological Society of America Memoir 158, p.161–176, doi:10.1130 / MEM158-p161.

[0164] Geiser, P. A., A. Lacazette, and J. Vermilye, 2012, Beyond ‘dots in a box’: An empirical view of reservoir permeability with tomographic fracture imaging: First Break, v. 30, p.63–69.

[0165] Geiser, P. A., and S. Sansone, 1981, Joints, microfractures, and the formation of solution cleavage in limestone: Geology, v.9, no.6, p.280–285, doi:10.1130 / 0091- 7613(1981)9<280:JMATFO>2.0.CO;2.

[0166] Geiser, P. A., N. Seeber, 2008, Three-dimensional seismo-tectonic imaging: An example from the Southern California Transverse Ranges, Journal of Structural Geology, vol. 30, issue 7, p.929-945.

[0167] Geiser, P. A., J. Vermilye, R. Scammell, and S. Roecker, 2006, Seismic used to directly map reservoir permeability fields: Oil & Gas Journal, v.18, accessed June 16, 2023, https: / / www.ogj.com / general-interest / companies / article / 17224322 / seismic-emission- tomography1-seismic-usedto-directly-map-reservoir-permeability-fields.

[0168] Geiser, P. A., P. E. Malin, S. E. Boyer, J. R. Geiser, 2023, Permeability Field Imaging: Mapping the GeoCritical Crust’s Permeability Field: AAPG Bulletin 107(9): 1581- 1608

[0169] Heffer, K. J., N. C. Koutsabeloulis, 1995, Stress effects on reservoir flow: - Numerical modeling used to reproduce field data, Geological Society, London, Special Publications 84 (1), 81-88

[0170] Janssen, C., F. C. Wagner, A. Zang, and G. Dresen, 2001, Fracture process zone in granite: A microstructural analysis: International Journal of Earth Sciences, v.90, no.1, p. 46–59, doi:10.1007 / s005310000157.LVM Ref.340101: 76-24 WO

[0171] Lacazette, A., J. Vermilye, S. Fereja, and C. Sicking, 2013, Ambient fracture imaging: A new passive seismic method: Society of Exploration Geophysicists / AAPG / Society of Petroleum Engineers Unconventional Resources Technology Conference, Denver, Colorado, August 12–14, 2013, p.2331–2340, doi:10.1190 / urtec2013- 244.

[0172] Lacazette, A. J., 1991, Natural hydraulic fracturing in the Bald Eagle sandstone in central Pennsylvania and the Ithaca siltstone at Watkins Glen, New York, Ph.D. dissertation, The Pennsylvania State University, State College, Pennsylvania, 226 p.

[0173] Leary, P. C., 1997, Rock as critical-point system and the inherent implausibility of reliable earthquake prediction: Geophysical Journal International, v.131, no.3, p.451–466, doi:10.1111 / j.1365-246X.1997.tb06589.x.

[0174] Malin, P. E., P. C. Leary, L. M. Cathles, and C. C. Barton, 2020, Observational and critical state physics descriptions of long-range flow structures: Geosciences, v.10, no.2, 50, 15 p., doi:10.3390 / geosciences10020050.

[0175] Michelena, R. J., J. R. Gilman, and C. K. Zahm, 2019, Seismic, geologic, geomechanics, and dynamic constraints in flow models of unconventional fractured reservoirs: Example from a south Texas field: The Leading Edge, v.38, no.2, p.116–122, doi:10.1190 / tle38020116.1.

[0176] N. S. Neidell and M. Turhan Taner, 1971, Semblance and other coherency measures for multichannel data, Geophysics, Vol.36, pp.482-497.

[0177] North, F. K., 1985, Petroleum geology: Boston, Allen & Unwin Inc., 607 p.

[0178] Scholz, C. H., 2002, The mechanics of earthquake faulting, 2nd ed., Cambridge, United Kingdom, Cambridge University Press, 471 p., doi:10.1017 / CBO9780511818516.

[0179] Sicking, C., and P. Malin, 2019, Fracture seismic: Mapping subsurface connectivity: Geosciences, v.9, no.12, 508, 34 p., doi:10.3390 / geosciences9120508.

[0180] Sicking, C., J. Vermilye, and A. Yaner, 2016, Pre-drill reservoir evaluation using passive seismic imaging: Society of Petroleum Engineers / AAPG / Society of ExplorationLVM Ref.340101: 76-24 WO Geophysicists Proceedings of the 4th Unconventional Resources Conference, San Antonio, Texas, August 1–3, 2016, URTEC-2460524-MS, 17 p., doi:10.15530 / urtec-2016-2460524.

[0181] Sicking, C., J. M. Vermilye, and P. M. Malin, 2019, Resonating fluid filled fractures in passive seismic, in Society of Exploration Geophysicists Technical Program Expanded Abstracts 2019: Tulsa, Oklahoma, Society of Exploration Geophysicists, p.3021– 3025, doi:10.1190 / segam2019-3214512.1.

[0182] Irina I. Tchebotareva, Alexiei V. Nikolaev, Haruo Sato (July, 2000) Seismic emission activity of Earth’s crust in Northern Kanto, Japan; Physics of the Earth and Planetary Interiors 120(3):167–182.

[0183] Vermilye, J., and C. Scholz, 1998, The process zone: A microstructural view of fault growth: Journal of Geophysical Research: Solid Earth, v.103, no. B6, p.12223–12237, doi:10.1029 / 98JB00957.

[0184] Ward, E. M. G., and J. W. Sears, 2007, Reinterpretation of fractures at Swift Reservoir, Rocky Mountain thrust front, Montana: Passage of a Jurassic forebulge?, in J. W. Sears, T. A. Harms, and C. A. Evenchick, eds., Whence the mountains? Inquiries into the evolution of orogenic systems: Washington, DC, Geological Society of America Special Papers 2007, v.433, p.197–210.

[0185] Yarushina, V. M., L. H. Wang, D. Connolly, G. Kocsis, I. Fæstø, S. Polteau, and A. Lakhlifi, 2022, Focused fluid-flow structures potentially caused by solitary porosity waves: Geology, v.50, no.2, p.179–183, doi:10.1130 / G49295.1.

[0186] Ziv, A., and A. M. Rubin, 2000, Static stress transfer and earthquake triggering: No lower threshold in sight?: Journal of Geophysical Research, v.105, no. B6, p.13631– 13642, doi:10.1029 / 2000JB900081. STATEMENTS REGARDING INCORPORATION BY REFERENCE AND VARIATIONS

[0187] All references throughout this application, for example patent documents including issued or granted patents or equivalents; patent application publications; and non- patent literature documents or other source material; are hereby incorporated by reference herein in their entireties, as though individually incorporated by reference, to the extent eachLVM Ref.340101: 76-24 WO reference is at least partially not inconsistent with the disclosure in this application (for example, a reference that is partially inconsistent is incorporated by reference except for the partially inconsistent portion of the reference).

[0188] The terms and expressions which have been employed herein are used as terms of description and not of limitation, and there is no intention in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention claimed. Thus, it should be understood that although the present invention has been specifically disclosed by preferred embodiments, exemplary embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended claims. The specific embodiments provided herein are examples of useful embodiments of the present invention and it will be apparent to one skilled in the art that the present invention may be carried out using a large number of variations of the devices, device components, methods steps set forth in the present description. As will be obvious to one of skill in the art, methods and devices useful for the present methods can include a large number of optional composition and processing elements and steps.

[0189] As used herein and in the appended claims, the singular forms "a", "an", and "the" include plural reference unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and equivalents thereof known to those skilled in the art. As well, the terms "a" (or "an"), "one or more" and "at least one" can be used interchangeably herein. It is also to be noted that the terms "comprising", "including", and "having" can be used interchangeably. The expression “of any of claims XX-YY” (wherein XX and YY refer to claim numbers) is intended to provide a multiple dependent claim in the alternative form, and in some embodiments is interchangeable with the expression “as in any one of claims XX-YY.”

[0190] Every device, system, combination of components, or method described or exemplified herein can be used to practice the invention, unless otherwise stated.LVM Ref.340101: 76-24 WO

[0191] Whenever a range is given in the specification, for example, a physical dimension or a time range, all intermediate ranges and subranges, as well as all individual values included in the ranges given are intended to be included in the disclosure.

[0192] All patents and publications mentioned in the specification are indicative of the levels of skill of those skilled in the art to which the invention pertains. References cited herein are incorporated by reference herein in their entirety to indicate the state of the art as of their publication or filing date and it is intended that this information can be employed herein, if needed, to exclude specific embodiments that are in the prior art.

[0193] As used herein, “comprising” is synonymous with "including," "containing," or "characterized by," and is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. As used herein, "consisting of" excludes any element, step, or ingredient not specified in the claim element. As used herein, "consisting essentially of" does not exclude materials or steps that do not materially affect the basic and novel characteristics of the claim. In each instance herein, any of the terms "comprising", "consisting essentially of" may be replaced with the other term. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein.

[0194] One of ordinary skill in the art will appreciate that devices, systems, and methods other than those specifically exemplified can be employed in the practice of the invention without resort to undue experimentation. All art-known functional equivalents, of any such devices and methods are intended to be included in this invention. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention claimed. Thus, it should be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended claims.

Claims

LVM Ref.340101: 76-24 WO Claims 1. A method for mapping a permeability field architecture of a study volume in country rock, the method comprising the steps of: acquiring seismic trace data from a network of seismic sensors above the study volume, wherein the study volume comprises a plurality of voxels, each voxel having a trace ensemble and an aperture; focusing the seismic trace data in each of the study volume voxel apertures, thereby forming for each voxel the voxel’s trace ensemble; calculating for each voxel of the study volume over a series of time intervals, value data streams comprising signal energy, coherent energy, and semblance value data streams from the acquired seismic trace data of each voxel trace ensemble; determining for each time interval of the series of time intervals, a static study volume (SSV) comprising the voxels of the study volume together with each voxel semblance value, signal energy value, and coherent energy value and their associated statistics, calculated from each voxel trace ensemble over the static study volume associated time interval; determining for each SSV a full activity volume (FAV) by identifying all voxels of the static study volume having semblance, signal energy and coherent energy values that satisfies a user-defined active voxel threshold condition; and mapping the permeability field by applying a surface extraction technique such as isosurface extraction, skeletonization, and / or color contouring isosurfaces within the entire FAV; thereby mapping the permeability field architecture of the study volume.

2. The method of claim 1, wherein the user-defined active voxel threshold condition is for an application selected from the group consisting of: locating regions of high permeability for the development and / or monitoring of an enhanced geothermal system, a CO2sequestration system, or a waste water injection site; locating proposed well bores for optimized fluid production; and monitoring the response to well bore stimulation and production.LVM Ref.340101: 76-24 WO 3. The method of any one of claims 1-2, wherein the user-defined active threshold condition is selected to be a more stringent condition such as a near well activity (NWA) threshold condition and / or a high activity threshold condition, thereby further identifying an area of the FAV that constitute a high activity permeability field (HaPF).

4. The method of any one of claims 1-3, wherein the step of calculating for each voxel of the study volume over a series of time intervals further comprises: calculating for each of the series of time intervals the signal energy and semblance values of the voxel; defining a coherent energy function ^^^ா^^^,^^^ to compute a coherent energy CE from the voxel's data, including the semblance ^^ and signal energy ^^, where CE is a measure of the energy emitted from the voxel rock and comprises the signal energy of the coherent traces of the voxel's trace ensemble; using the defined coherent energy function ^^^ா^^^,^^^ to calculate for each of the series of time intervals the coherent energy of the voxel's trace ensemble.

5. The method of claim 4, wherein the coherent energy function comprises: defining a Coherent Energy Percentage function ^^^ா^^^^^, whose argument is semblance ^^ and whose value is a percentage of the voxel's signal energy ^^ that constitutes the signal energy CE of the coherent traces of the voxel's trace ensemble; wherein the coherent energy percentage function fCEP(S) is used to calculate the coherent energy CE of a voxel from the voxel’s semblance S and signal energy E by means of the Coherent Energy Equation CE = ^^^ா^^^,^^^ = ^^^ா^^^^^ ൈ ^^.

6. The method of claim 5, further comprising the step of defining the Coherent Energy Percentage function ^^^ா^^^^^ by: deriving from empirical studies of FAVs, or from the studies of a Synthetic Trace Ensemble System, or both, a mathematical or tabular relationship between the semblance ^^ and the signal energy ^^ of a voxel's or study's trace ensemble and the signal energy CE of the coherent traces of the trace ensemble and using that relationship to define ^^^ா^^^^^; orLVM Ref.340101: 76-24 WO defining a Default Coherent Energy Percentage function ^^^ா^^^^^ as a quadratic polynomial ^^ଶ ^ ^^ – ^^, where C is a user-specified value in the range [0.5, 1.0] and^^ ^ ^^^ where ^^^ is the active voxel semblance threshold value; ordefining ^^^ா^^^^^ ൌ ^^ ൈ ^^ଶ ^ ^^ ൈ ^^ ^ ^^ where ^^, ^^, ^^ are user-specified constantssatisfying a Quadratic Coherent Energy Percentage Function Conditions.

7. The method of any one of claims 1- 6, further comprising a change in a stress field of the study volume, wherein the change in the stress field comprises a change in a transient and induced stress fields in the study volume.

8. The method of any one of claims 1-7, wherein the study volume comprises any sub- surface volume of rock selected from the group consisting of: a geologic formation, a reservoir, a target volume for Enhance Geothermal Systems (EGS), CO2 Sequestration Systems (CO2SS), Energy Storage Systems (ESS), and Waste Water Injection Site (WWIS).

9. The method of any one of claims 1-8, wherein the study volume includes fracture systems and zones of high energy radiation.

10. The method of any one of claims 1-9, wherein the network of seismic sensors comprises a geophone field.

11. The method of any one of claims 1-10, further comprising the step of introducing a seismic energy perturbation to the country rock.

12. The method of any one of claims 1-11, wherein the step of mapping the permeability field further comprises applying one or more extractive techniques selected from the group consisting of: 3D color contouring of the FAV voxel coherent energy, isosurface extraction of the coherent energy parameter, skeletonization of the coherent energy, and an enhanced peak picker tool to find local areas of a FAV of connected, high activity voxels that form connected ridges and / or ellipsoids.

13. The method of any one of claims 1-12, further comprising the step of determining a maximum number of NWA voxels.

14. The method of claim 13, wherein the maximum number of NWA voxels further comprises a maximum number of voxels in direct contact with a wellbore or a proposedLVM Ref.340101: 76-24 WO wellbore location or indirectly in contact with a wellbore or proposed wellbore location through a chain of connected NWA voxels.

15. The method of any one of claims 12-14, further comprising the step of identifying an optimal well bore location corresponding to a proposed well bore location having a highest maximum number of NWA voxels.

16. The method of any one of claims 1-15, used to: store a fluid in the study volume; recover a fluid contained from the study volume; or exchange heat from a thermal exchange fluid flowing into and out of the study volume that is used in a geothermal process.

17. The method of any one of claims 1-16, wherein the step of acquiring the seismic traces comprises using: a 3D seismic survey; a geophone surface array; a geophone buried array; and / or any combination thereof.

18. The method of any one of claims 1-17, used for a fluid recovery, wherein the fluid comprises hydrocarbon or water.

19. The method of any one of claims 1-18, wherein each voxel has a volume of between 100 m3and 10ଽm3.

20. The method of any one of claims 1-19, wherein the study volume has a volume between 0.1 ^^^^ଷand 1000 ^^^^ଷ.

21. The method of any one of claims 1-20, further comprising the step of populating a 3D volume representation of the static study volume with only the active voxels, thereby visualizing the permeability field architecture of the FAV of the study volume.

22. The method of any one of claims 1-21, further comprising the step of drilling a well bore in the study volume at a location corresponding to a proposed well bore location determined from the mapped permeability field architecture of the study volume.

23. The method of any one of claims 1-22, wherein the physical attribute associated with a voxel is an energy-related physical property such as power or work in reference to theLVM Ref.340101: 76-24 WO response of rock to its changing stress environment and used to map the permeability field of the study volume.

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