Porosity measurement from nuclear spectroscopy

Abstract

Systems and methods presented herein support porosity estimation using neutron-induced gamma ray spectra. For example, the systems and methods presented herein include receiving, via a control and data acquisition system, data relating to an energy spectrum of gamma rays captured by one or more gamma ray detectors of a neutron-induced gamma ray spectral logging tool. The method further includes deriving, via the control and data acquisition system, one or more spectral yields related to one or more elemental components from the data related to the energy spectrum of the gamma ray. The method further includes estimating, via the control and data acquisition system, a measurement of porosity based on the one or more spectral yields associated with the one or more elemental components.

Description

[0001] Cross-reference paragraphs

[0002] This application claims the benefit of U.S. non-provisional application No. 17 / 929,446, filed on September 2, 2022, entitled “POROSITY MEA SUREMENTS FROMNUCLEAR SPECTROSCOPY,” the disclosure of which is hereby incorporated by reference herein. Background Art

[0003] The present disclosure generally relates to neutron induced gamma ray spectroscopy and the estimation of porosity and / or hydrogen index (HI) in bulk media traversed by a wellbore. More specifically, embodiments described herein use at least one of an energy spectrum and a resulting spectral yield as a primary input for estimating porosity or HI.

[0004] This section is intended to introduce the reader to various aspects of the technology that may be related to various aspects of the present technology, which are described and / or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Therefore, it should be understood that these statements should be interpreted in this light and are not admissions as prior art.

[0005] Formation porosity and HI are important measurements for characterizing hydrocarbon reservoirs. Porosity represents the volume fraction of bulk rock that is occupied by pores within a solid matrix. It is also common to divide total porosity into subunits (e.g., effective porosity, free fluid volume, bound fluid volume, etc.). HI is usually defined as the ratio of the molar concentration of hydrogen atoms in bulk rock to the molar concentration of hydrogen in pure water at standard temperature and pressure. Summary of the invention

[0006] The following describes an overview of certain embodiments disclosed herein. It should be understood that these aspects are presented only to provide the reader with a brief overview of these specific embodiments and that these aspects are not intended to limit the scope of the present disclosure. In fact, the present disclosure may encompass a number of aspects that may not be described below.

[0007] Certain embodiments described herein include a method comprising receiving, via a control and data acquisition system, data relating to spectra of gamma rays captured by one or more gamma ray detectors of a neutron induced gamma ray spectroscopy logging tool. The method also comprises deriving, via the control and data acquisition system, one or more spectral yields relating to one or more elemental components from the data relating to the energy spectrum of the gamma rays. The method also comprises estimating, via the control and data acquisition system, a measurement of porosity based on the one or more spectral yields relating to the one or more elemental components.

[0008] In addition, certain embodiments described herein include a system comprising a neutron induced gamma ray spectroscopy logging tool and a control and data acquisition system. The neutron induced gamma ray spectroscopy logging tool comprises: a neutron source configured to generate neutrons to induce a gamma ray energy spectrum; and one or more gamma ray detectors configured to detect the energy spectrum of gamma rays. The control and data acquisition system is configured to receive data related to the energy spectrum of gamma rays captured by one or more gamma ray detectors of the neutron induced gamma ray spectroscopy logging tool. The control and data acquisition system is also configured to derive one or more spectral yields related to one or more elemental components from the data related to the energy spectrum of the gamma rays. The control and data acquisition system is also configured to estimate a measured value of porosity based on the one or more spectral yields related to one or more elemental components.

[0009] In addition, certain embodiments described herein include a control and data acquisition system comprising one or more processors configured to execute instructions stored on a memory medium of the control and data acquisition system, wherein the instructions, when executed by the one or more processors, cause the control and data acquisition system to receive data relating to an energy spectrum of gamma rays captured by one or more gamma ray detectors of a neutron induced gamma ray spectroscopy logging tool, derive one or more spectral yields relating to one or more elemental components from the data relating to the energy spectrum of the gamma rays, and estimate a measurement of porosity based on the one or more spectral yields relating to the one or more elemental components.

[0010] Various improvements may be made to the above features with respect to various aspects of the present disclosure. Additional features may also be incorporated into these various aspects as well. These improvements and additional features may exist independently or in any combination. For example, various features discussed below with respect to one or more of the illustrated embodiments may be incorporated into any of the above aspects of the present disclosure individually or in any combination. The brief overview presented above is intended to familiarize the reader with certain aspects and contexts of the embodiments of the present disclosure without limiting the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Various aspects of the present disclosure may be better understood after reading the following detailed description and after referring to the accompanying drawings, in which:

[0012] Figure 1 A drilling system having a neutron induced gamma ray spectroscopy logging tool according to an embodiment of the present disclosure is shown;

[0013] Figure 2A schematic block diagram side view of an illustrative embodiment of an LWD module according to an embodiment of the present disclosure is shown, the LWD module being or including a neutron induced gamma ray spectroscopy logging tool;

[0014] Figure 3 shows examples of inelastic and capture spectra from a neutron induced gamma ray spectroscopy logging tool according to an embodiment of the present disclosure, showing gamma ray spectra of various elemental components from thermal neutron radiation capture and inelastic reactions;

[0015] Figure 4 shows an example of epithermal neutron yield in a laboratory formation plotted relative to real formation porosity in accordance with an embodiment of the present disclosure;

[0016] FIG. 5A to FIG. 5C shows example spectral data in a cross plot including inelastic tool background yield and hydrogen yield and a method of estimating porosity according to an embodiment of the present disclosure; and

[0017] Figure 6 is a flow chart of a method of estimating porosity using neutron induced gamma ray spectroscopy according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0018] One or more specific embodiments of the present disclosure will be described below. These described embodiments are examples of currently disclosed technologies. In addition, in order to provide a brief description of these embodiments, all features of the actual implementation may not be described in the specification. It should be understood that, as in any engineering or design project, when developing any such actual or method, many decisions related to the specific implementation must be made to achieve the specific goals of the developers, such as complying with system-related and business-related constraints, which may vary from implementation to implementation. In addition, it should be understood that such development work may be complex and time-consuming, but for ordinary technicians who benefit from the present disclosure, this will still be a routine task in design, fabrication, and production.

[0019] When introducing elements of various embodiments of the present disclosure, the articles "a," "an," and "the" are intended to mean that there are one or more of the elements. The terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements in addition to the listed elements. Additionally, it should be understood that references to "one embodiment" or "an embodiment" of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features.

[0020] Rock properties (e.g., matrix properties) may affect the overall formation response of well log measurements, and to this end, it may be necessary to determine accurate rock properties in order to accurately interpret well log measurements of certain formation properties (such as porosity, hydrogen index (HI), saturation, and permeability). For example, rock properties such as matrix particle density can be used to provide an accurate determination of formation porosity using measurements of formation bulk density. In at least some instances, certain rock properties may be difficult to measure directly or otherwise unobtainable, but may be inferred from other measurable properties of the rock, such as element concentrations measured by downhole neutron spectroscopy (such as neutron induced gamma ray spectroscopy). Neutron induced gamma ray spectroscopy can be used to derive certain rock properties of a formation based on element concentrations within a geological substrate. In neutron induced gamma ray spectroscopy, fast neutrons and thermal neutrons generated by natural radioactive materials or pulsed neutron generators contained within the housing of a logging probe (e.g., a portion of a logging tool including a sensor) may interact with element nuclei in a geological formation and produce gamma radiation in a local volume around the logging probe through inelastic nuclear reactions and neutron capture reactions. The generated gamma rays pass through the geological formation, and some of the gamma rays are detected by a detector (e.g., a sensor) contained within the housing of the logging probe. The detector signal is used to generate a spectrum indicating the contribution of gamma rays, which represent element nuclei in the formation. The gamma ray spectra associated with inelastic scattering and thermal neutron capture can be quantified separately. The inelastic and capture spectra can be plotted as a function of count rate versus energy. The spectrum contains information about the identity of the element (i.e., the characteristic energy from the gamma rays) and about the concentration of the element (i.e., the number or relative number from the counts).

[0021] Regardless, mathematical methods can be used to quantitatively estimate or infer certain rock properties (e.g., matrix properties) directly from elemental concentrations associated with certain elemental components (such as silicon, calcium, iron, magnesium, and sulfur). These rock properties include, for example, one or more mineral concentrations in the rock matrix, matrix grain density, matrix neutron porosity response, and aluminum concentration in the rock matrix.

[0022] Conventional methods for estimating porosity and HI rely on logarithmic measurements of bulk density, neutron porosity, nuclear magnetic resonance, or some combination thereof. For example, total porosity can be calculated from bulk density by inputting the density of the solid rock matrix and the pore fluid composition. In addition, measurements of neutron transport can also be used to infer porosity or HI. The porosity or HI estimate can then be calibrated based on the count rate of one or more detectors. In conventional neutron porosity measurements, a neutron source emits neutrons into the surrounding medium, and the detector responds to neutrons that reach the thermal or epithermal energy region. These porosity measurements may be variously referred to as TNPH, NPHI, NPOR, APLC, and other mnemonics. Other neutron porosity techniques are based on the emission of neutrons from a source and the detection of the total count rate of gamma rays within a specific time window on one or more detectors. The latter technique does not apply an energy spectrum to gamma rays. These porosity measurements may be referred to as TPHI or other mnemonics. Nuclear magnetic resonance (NMR) provides another technique for measuring porosity or HI. The total hydrogen content in the formation, the distribution of pore sizes, and other information about the fluids can be inferred from the amplitude of the NMR signal and its relaxation rate. Generally speaking, in certain environments, operational challenges prevent the use of these mature techniques to obtain porosity and HI logs.

[0023] Embodiments described herein provide systems and methods for estimating porosity based on neutron-induced gamma-ray spectroscopy measurements. For example, certain embodiments described herein use the spectral yield of epithermal neutrons captured in a spectral detector, which can be calibrated based on formation porosity, HI or other related properties. In addition, certain embodiments described herein use the spectral yield of hydrogen as the basis for measuring formation porosity, HI or other related properties. Calibration may take into account other environmental effects, and the algorithm may be designed empirically, or machine learning may be utilized. In addition, the systems and methods described herein may be derived based on data from a laboratory, computer modeling or downhole recorded data.

[0024] Considering the foregoing, Figure 1 A drilling system 10 is shown with a neutron induced gamma ray spectroscopy logging tool, as described in more detail herein. The drilling system 10 can be used to drill a well in a geological formation 12 and obtain gamma ray spectroscopy measurements that can be used to identify characteristics of the well. Figure 1In the drilling system 10 shown in FIG. 1 , a drill rig 14 located at the surface 16 may rotate a drill string 18 having a drill bit 20 at its lower end. As the drill bit 20 rotates, a drilling fluid pump 22 is used to pump a drilling fluid 24 (commonly referred to as "mud" or "drilling mud") downwardly through the center of the drill string 18 to the drill bit 20 in the direction of the arrows. The drilling fluid 24, which is used to cool and lubricate the drill bit 20, exits the drill string 18 through the drill bit 20. The drilling fluid 24 then carries drill cuttings away from the bottom of the borehole 26 as it flows back to the surface 16, as indicated by the arrows passing through the annulus 30 between the drill string 18 and the formation 12. However, as described above, as the drilling fluid 24 flows through the annulus 30 between the drill string 18 and the formation 12, the drilling fluid 24 may begin to invade and mix with fluid stored in the formation 12, which may be referred to as formation fluid (e.g., natural gas or oil). At the surface 16 , the returning drilling fluid 24 may be filtered and transported back to the mud pit 32 for reuse.

[0025] like Figure 1 As shown in , the lower end of the drill string 18 includes a bottom hole assembly (BHA) 34, which may include a drill bit 20 and various downhole tools. The downhole tools can collect a variety of information related to the geological formation 12 and / or the drilling status. For example, a measurement while drilling (MWD) module 36 can measure certain drilling parameters, such as temperature, pressure, direction of the drilling tool, etc. Similarly, a logging while drilling (LWD) module 38 can measure the physical properties of the geological formation 12, such as density, porosity, resistivity, lithology, etc.

[0026] The LWD module 38 may collect a variety of data 40 that may be stored and processed within the LWD module 38 or as described herein. Figure 1 , can be sent to the surface for processing. In an example of the present disclosure, the LWD module 38 may include a neutron induced gamma ray spectroscopy logging tool that can detect the energy of formation gamma rays produced when neutrons are emitted into the well. The energy range of the detected gamma rays can be visualized as a spectrum of the detected gamma rays. The collected data 40 may include counts and / or detected energies of neutrons and gamma rays arriving at corresponding detectors in the LWD module 38. It should be understood that although Figure 1 The embodiment shown in the figure is intended to collect data via the LWD module 38, but in other embodiments, a wireline tool can be used as a delivery mode. In other words, the neutron induced gamma ray spectroscopy logging tool can be deployed into the borehole 26 via logging while drilling (LWD), wireline, coiled tubing, or any other suitable downhole delivery mode.

[0027] The data 40 may be sent to a data processing system 44 via a control and data acquisition system 42. The control and data acquisition system 42 may receive the data 40 in any suitable manner. In certain embodiments, the control and data acquisition system 42 may transmit the data 40 via an electrical signal pulsed through the geological formation 12 or via mud pulse telemetry using the drilling fluid 24. In other embodiments, the data 40 may be retrieved directly from the LWD module 38 when the LWD module 38 returns to the surface. As described in more detail herein, the control and data acquisition system 42 may be configured to estimate porosity using the neutron induced gamma ray spectroscopy data 40 provided by the LWD module 38. Additionally, in certain embodiments, the control and data acquisition system 42 may be configured to control any and all operating parameters of the BHA 34, including, but not limited to, the operation of the neutron induced gamma ray spectroscopy logging tool of the LWD module 38, as described in more detail herein.

[0028] In certain embodiments, the data processing system 44 may include a processor 46, a memory 48, a storage device 50, and / or a display 52. ​​The data processing system 44 may use the data 40 to determine various properties of the formation 12 using any suitable technique. As will be described in more detail herein, the LWD module 38 may use certain selected materials to reduce signal contamination caused by stray neutrons. Therefore, when the data processing system 44 processes the data 40, the determined formation properties may be more accurate and / or precise than otherwise. To process the data 40, the processor 46 may execute instructions stored in the memory 48 and / or the storage device 50. To this end, the memory 48 and / or the storage device 50 of the data processing system 44 may be any suitable article capable of storing instructions. To name only a few examples, the memory 48 and / or the storage device 50 may be a ROM memory, a random access memory (RAM), a flash memory, an optical storage medium, or a hard drive. The display 52 may be any suitable electronic display capable of displaying logs and / or other information related to the properties of the formation 12 measured by the LWD module 38. It should be appreciated that although the data processing system 44 is shown as being located at the surface, the data processing system 44 may also be located in the LWD module 38. In such embodiments, some of the data 40 may be processed in the LWD module 38, and the data 40 may be stored in the LWD module 38, while some of the data 40 may be sent to the surface in real time. This may be particularly true in LWD, where only a limited amount of data 40 may be transmitted to the surface during drilling or reaming operations.

[0029] As described in greater detail herein, the LWD module 38 may be or include a neutron induced gamma ray spectroscopy logging tool. Figure 2A schematic block diagram side view of an illustrative embodiment of an LWD module 38 is shown, which is a neutron induced gamma ray spectroscopic logging tool 54 or includes the neutron induced gamma ray spectroscopic logging tool. In certain embodiments, the spectroscopic logging tool 54 may include a chassis 56, a collar 58, and a flow tube 60 extending through the spectroscopic logging tool 54. In certain embodiments, a neutron source 62 is located at a first position within the spectroscopic logging tool 54, and one or more gamma ray detectors 64 are located at a second position axially spaced from the neutron source 62. In addition, in certain embodiments, a neutron shield 66 (e.g., a boron shield) may be radially disposed around the spectroscopic logging tool 54 at or near the second position. Details regarding this embodiment and other embodiments of the spectroscopic logging tool employing the general configuration or aspects of the LWD module 38 and the spectroscopic logging tool 54 are contemplated for use in any suitable delivery means, such as cable, coiled tubing, logging while drilling (LWD), and the like. Furthermore, additional equipment may be used to obtain information about the environment, such as the sigma of the formation 12, the sigma of the drilling fluid 24, density, borehole size, and slowdown length.

[0030] In general, the neutrons emitted by the neutron source 62 may interact with the surrounding formation 12, thereby generating gamma rays through inelastic scattering and / or neutron capture. Inelastic scattering may generate gamma rays by interacting with fast neutrons and elements 12 of the formation. Neutron capture may generate gamma rays by capturing mainly thermal neutrons and epithermal neutrons by atomic nuclei. The gamma rays formed may be detected by a gamma ray detector 64. In certain embodiments, the gamma ray detector 64 may be a scintillation detector including a scintillation crystal and a photomultiplier tube. In certain embodiments, the gamma ray detector 64 may detect the spectrum, i.e., the energy range, of the formation gamma rays. However, in certain embodiments, the gamma ray detector 64 may detect gamma rays that appear in the borehole 26 or the spectral logging tool 54 itself. In fact, in certain embodiments, the neutrons emitted by the neutron source 62 may scatter through or around the neutron shield 66 and other surrounding materials, thereby generating gamma rays from unexpected locations. For example, other gamma rays may be generated by reactions of neutrons with elements of the drilling fluid 24 in the borehole 26, the neutron shield 66, the chassis 56, the collar 58, the gamma ray detector 64 itself, the drilling fluid 24 within the flow tube 60, and / or the flow tube 60 itself, to name just a few locations where additional gamma rays may be generated. Gamma rays generated by these reactions outside the formation 12 may not provide significant information about the properties of the geological formation 12. For this reason, in certain embodiments, the spectra of these gamma rays generated outside the geological formation 12 may represent noise that the control and data acquisition system 42 should subtract from the overall spectral signal. Otherwise, the presence of this background noise may increase the uncertainty of the gamma ray spectrum measurement.

[0031] Figure 2 The nuclear spectrum provided by the spectroscopic logging tool 54 shown in the figure can provide rich information about the elemental composition of the materials surrounding the spectroscopic logging tool 54. In certain embodiments, the electronic pulse neutron generator (PNG) of the neutron source 62 can produce high-energy neutron pulses that interact with the surrounding atomic nuclei to induce gamma rays. In general, the gamma ray detector 64 of the spectroscopic logging tool 54 detects the energy spectrum of these gamma rays. As described in more detail herein, the control and data acquisition system 42 can analyze the energy spectrum to provide separate spectra of inelastic reactions and capture reactions, each spectrum carrying complementary information from different element groups (e.g., the elemental composition of the surrounding formation 12). The elemental yields from these spectra respond to the geochemical properties of the formation rocks as well as the solid organic matter, pore fluids, and the borehole 26.

[0032] Figure 3 An example of inelastic and captured spectra from the spectral logging tool 54 is shown, showing gamma ray spectra of various elemental components from thermal neutron radiation capture (left figure) and inelastic reaction (right figure). As shown, in certain embodiments, the thermal neutron radiation capture elemental components may include magnesium (Mg), sulfur (S), titanium (Ti), aluminum (Al), potassium (K), calcium (Ca), silicon (Si), iron (Fe), chlorine (Cl), gadolinium (Gd), hydrogen (H), and the inelastic reaction elemental components may include magnesium (Mg), iron (Fe), sulfur (S), carbon (C), aluminum (Al), silicon (Si), calcium (Ca) and oxygen (O). In addition, the capture tool background (CTB) and the inelastic tool background (ITB) are also shown in the corresponding charts.

[0033] The spectroscopic analysis described herein can provide information on formation chemistry, mineralogy, organic carbon, and chlorine concentrations. Total pore volume or hydrogen index (HI) is not typically the focus of spectral interpretation. However, the raw spectral yields have been found to respond to formation porosity and hydrogen content. Several of the most promising candidate yields have been found and are described in more detail below.

[0034] The embodiments described herein are configured to estimate a measure of porosity based on an algorithm (or set of algorithms) that uses one or more spectral yields derived from the energy spectrum in the neutron induced gamma ray spectrum implemented by the spectroscopic logging tool 54. In certain embodiments, the porosity is the volume fraction of pore space in the bulk formation rock of the surrounding formation 12. In other embodiments, the porosity is the HI in the bulk formation rock of the surrounding formation 12.

[0035] In certain embodiments, the spectral yield is the yield associated with gamma rays induced by epithermal neutrons captured primarily by the gamma-ray detector 64 of the spectral logging tool 54. In other embodiments, the spectral yield is the yield of gamma rays from neutrons captured by hydrogen. In certain embodiments, the spectral yield originates from the energy spectrum of gamma rays induced by inelastic reactions of atomic nuclei with fast neutrons, also referred to as the inelastic spectrum. In other embodiments, the spectral yield originates from the energy spectrum of gamma rays induced by radiative capture of neutrons by atomic nuclei, also referred to as the capture spectrum. In certain embodiments, the spectral yield represents the relative fraction of the energy spectrum associated with a specific elemental component. Additionally, in certain embodiments, the spectral yield represents the absolute count rate of the contribution of a specific element or spectral component to the overall energy spectrum.

[0036] In certain embodiments, the algorithm takes into account environmental effects near the spectroscopic logging tool 54, including but not limited to HI of pore fluids and formation matrix, HI of borehole fluids, formation lithology, formation and borehole salinity, temperature, pressure, borehole size, tool spacing, and invasion. In certain embodiments, some of the environmental effects used to correct for porosity can be determined from the spectroscopic measurement itself (e.g., detection of gamma rays), including but not limited to formation lithology and formation and borehole salinity.

[0037] In some embodiments, the algorithm may be derived at least in part based on laboratory data, computer modeling, downhole log data, or some combination thereof. Additionally, in some embodiments, the algorithm may be designed empirically based at least in part on human judgment. Additionally, in some embodiments, the algorithm may be based at least in part on machine learning, including but not limited to techniques such as multiple linear regression, neural networks, support vector machines, decision trees, extended neural network architectures that may include recurrent networks, long short-term memory (LSTM) networks, attention models, or integrated methods combining multiple instances of the aforementioned techniques.

[0038] In some embodiments, neutrons can be generated by a radiochemical neutron source 62, including but not limited to americium-beryllium (AmBe) or californium-252 (Cf-252). In other embodiments, neutrons can be generated by a pulsed neutron generator 62. As described above, in some embodiments, spectral analysis can be performed based on an energy spectrum acquired at one or more gamma-ray detectors 64 of the spectral logging tool 54. In some embodiments, one or more gamma-ray detectors 64 can include a scintillator detector. In addition, in some embodiments, one or more gamma-ray detectors 64 can include a solid-state detector. In some embodiments, the aforementioned instruments for obtaining spectral measurements can be deployed via logging while drilling (LWD), cable, continuous tubing, or other downhole delivery modes.

[0039] Epithermal neutron yield

[0040] As described in more detail herein, in certain embodiments, the inelastic spectrum may contain a component of gamma rays that is primarily produced by capturing epithermal neutrons within the scintillator crystal of the gamma ray detector 64 of the spectroscopic logging tool 54 during or after a neutron burst. The corresponding spectral yield is a representation of the number of epithermal neutrons at the gamma ray detector 64 of the spectroscopic logging tool 54. The fact that hydrogen can slow down neutrons most effectively forms the basis of classical neutron porosity measurements. From this perspective, the spectral yield can be interpreted as a single-detector, uncompensated epithermal neutron porosity measurement. The embodiments described herein use such measurements to estimate porosity, as described in more detail herein. In certain embodiments, using element standards that represent the spectral shape of gamma rays produced by capturing epithermal neutrons inside the gamma ray detector 64, spectrally derived epithermal neutron measurements using the gamma ray detector 64 can be achieved.

[0041] The spectral yield may respond to the distribution of all hydrogen around the spectral logging tool 54. In addition to formation porosity, the spectral yield may be affected by the HI of the pore fluid and formation matrix, the HI of the borehole fluid, the borehole size, tool spacing, and invasion. Figure 4 An example of epithermal neutron yield in a laboratory formation is shown, plotted against true formation porosity (pu). The graph shows true formation porosity (pu) versus the spectral yield of the epithermal tool background measured by the spectral logging tool 54 in the laboratory formation. Each borehole diameter (BHD) 68, 70, 72 (i.e., 6 inches, 8.5 inches, and 12 inches, respectively) shows a clear trend in porosity versus epithermal neutron yield.

[0042] FIG. 5A to FIG. 5C Example spectral data including inelastic tool background yield and hydrogen yield in a cross plot and a method for estimating porosity are shown. Specifically, Figure 5A is a cross plot 74 showing the correlation between thermal neutron porosity (TNPH_LIM) from a dedicated neutron porosity tool and inelastic tool background yield (IYDB) from a spectral logging tool. Figure 5B is a cross-plot 76 showing the correlation between the inelastic tool background yield (IYDB) and the total porosity from the NMR tool (TCMR). In addition, Figure 5C is a cross-plot 78 showing the correlation between trapped hydrogen yield (CYHY) and total porosity (TCMR) from the NMR tool.

[0043] It is worth noting that, in general, there are two separate inelastic tool background yields and inelastic element standard spectra. The first, whose yield is designated IYTB, involves the detection of gamma rays produced primarily by inelastic scattering reactions of fast neutrons that produce elements that are part of the body of the logging probe, and which are mostly from various metal alloys. This spectral yield is typically 40% to 50% of the measured inelastic spectrum. This yield has very little dependence on the environment, which in practice makes it relatively difficult to isolate its unique spectral response, which is required for spectral analysis. The second, whose yield is designated IYDB, involves the detection of gamma rays produced primarily by epithermal neutron capture inside the detector crystal itself. This yield is typically less than half of the IYTB yield and is relatively dependent on the environment. This yield transforms the detector crystal into an epithermal neutron detector that is very sensitive to formation porosity and hydrogen index.

[0044] In addition, it should be noted that the gamma-ray spectrum consists of at least six separate components: (a) gamma rays produced by inelastic scattering of high-energy neutrons; (b) gamma rays produced by capturing epithermal neutrons; (c) gamma rays produced by neutron-induced nuclear reactions, which change the nuclei of atoms into different elements and produce gamma rays that decay rapidly; (d) gamma rays produced by neutron-induced nuclear reactions, which change the nuclei of atoms into different elements and produce gamma rays that do not decay rapidly; (e) gamma rays produced by capturing thermal neutrons during the burst and produced by previous bursts; and (f) gamma rays from naturally radioactive elements. In certain embodiments, gamma rays from components d, e, and f can be removed from the burst spectrum prior to analysis using measurement gates judiciously selected relative to various different times of the burst. In addition, gamma rays from components a, b, and c appear only during the neutron burst, and these gamma rays are often referred to as "inelastic," even though only component a is truly inelastic.

[0045] As a relative yield, epithermal neutron yield may also be affected by the concentrations of all other elements and spectral components. In certain embodiments, the spectral yield can be calculated as the absolute count rate for each spectral component by incorporating a neutron monitor that provides neutron output to normalize the spectral analysis. In certain embodiments, porosity estimation can use either relative yield or absolute spectral count rate.

[0046] Epithermal neutron yield characterization of porosity or HI may be a globally optimized algorithm (or set of algorithms) for many different logging environments, or it may be a fit-for-purpose solution whose applicability will be limited to a limited set of logging environments.

[0047] It is expected that the measurement will respond to all hydrogen in the formation 12, including, for example, hydrogen (protons) whose T2 relaxation time is too short to appear in the nuclear magnetic resonance (NMR) porosity. Therefore, if heavy oil, tar, or kerogen is present in the formation 12, the spectral HI will be greater than the NMR porosity. If the HI of the invading brine is low, the spectral HI may also be lower than the total formation porosity. Conversely, due to the effects of high formation atomic density in some cases, the spectral HI reading may be higher than the total porosity.

[0048] Hydrogen capture output

[0049] Hydrogen is measured in the capture spectrum. The primary hydrogen yield, called the hydrogen capture yield, contains gamma rays from hydrogen from both the formation 12 and the borehole 26. The hydrogen capture yield may respond to formation porosity as well as the other effects described above: HI of the pore fluid and formation matrix, HI of the borehole fluid, borehole size, tool spacing, and invasion.

[0050] Additionally, relative capture yields (such as hydrogen capture yield) will be affected by competition for neutrons from other thermal absorbers in the surrounding material. From this perspective, hydrogen capture yield can be interpreted as a single-detector, uncompensated thermal porosity measurement.

[0051] The second hydrogen yield (i.e., the hydrogen capture yield) carries more information, having a characteristic spectral shape different from the primary hydrogen spectrum and representing hydrogen gamma rays that have undergone additional scattering in the formation 12. In certain embodiments, differential scattering techniques may be used to separate other elements (such as chlorine) in the formation and borehole components. Additionally, in certain embodiments, this formation / borehole technique may also be applied to hydrogen to better isolate the formation hydrogen yield.

[0052] In certain embodiments, by incorporating a neutron monitor that provides neutron output to normalize the spectral analysis, the spectral yield can be calculated as the absolute count rate for each spectral component. Porosity estimates can use either relative yields or absolute spectral count rates. The above-mentioned limitations and differences in suitability for use with respect to NMR proton responses are also relevant to spectral hydrogen yields.

[0053] Algorithm structure

[0054] In certain embodiments, the spectral yield characterization of porosity or HI may be a globally optimized algorithm (or set of algorithms) for many different logging environments, or it may be a fit-for-purpose solution whose applicability will be limited to a limited set of logging environments.

[0055] In certain embodiments, calibration of the spectral yield of porosity or HI can be performed by an algorithm designed empirically with human judgment, can be the product of machine learning, or some combination thereof. Machine learning methods can include, but are not limited to, techniques such as multiple linear regression, neural networks, support vector machines, decision trees, extended neural network architectures that can include recurrent networks, long short-term memory (LSTM) networks, attention models, or integrated methods that combine multiple instances of the above-mentioned techniques.

[0056] Additionally, in certain embodiments, the algorithm may be derived based on any combination of laboratory measurements, computer simulations, and downhole log data. Additionally, in certain embodiments, the input measurements may include any of the previously mentioned spectral yields (e.g., epithermal neutron yield, hydrogen capture yield, etc.) or additional spectrally derived measurements. Additionally, in certain embodiments, the inputs may also include features such as borehole diameter, borehole fluid density, and other aspects of the environment that affect the spectral yield.

[0057] Figure 6 8 is a flow chart of a method 80 for estimating porosity using neutron induced gamma ray spectroscopy, as described in more detail herein. In certain embodiments, the method 80 may include receiving data 40 related to an energy spectrum of gamma rays captured by one or more gamma ray detectors 64 of a neutron induced gamma ray spectroscopy logging tool 54 via a control and data acquisition system 42 (box 82). Additionally, in certain embodiments, the method 80 may include deriving one or more spectral yields related to one or more elemental components from the data 40 related to the energy spectrum of gamma rays via the control and data acquisition system 42 (box 84). Additionally, in certain embodiments, the method 80 may include estimating a measured value of porosity based on one or more spectral yields related to one or more elemental components via the control and data acquisition system 42 (box 86).

[0058] In certain embodiments, the method 80 may include deploying a neutron induced gamma ray spectroscopy logging tool 54 into a borehole 26 that extends downhole through the geological formation 12 via logging while drilling (LWD), wireline, coiled tubing, or other downhole delivery mode. Additionally, in certain embodiments, the one or more spectral yields associated with the one or more elemental components include one or more yields of one or more gamma rays produced by capturing epithermal neutrons. In other embodiments, the one or more spectral yields associated with the one or more elemental components include one or more hydrogen yields captured by one or more gamma ray detectors 64 of the neutron induced gamma ray spectroscopy logging tool 54.

[0059] Additionally, in certain embodiments, method 80 may include inducing an energy spectrum of gamma rays via an inelastic reaction of atomic nuclei with fast neutrons. In other embodiments, method 80 may include inducing an energy spectrum of gamma rays via radiative capture of neutrons by atomic nuclei. Additionally, in certain embodiments, one or more spectral yields associated with the one or more elemental components represent one or more relative fractions of an energy spectrum of gamma rays associated with corresponding elemental components of the one or more elemental components. Additionally, in certain embodiments, one or more spectral yields associated with the one or more elemental components represent one or more absolute count rates of contributions of corresponding elemental components of the one or more elemental components to the total energy spectrum of gamma rays.

[0060] Additionally, in certain embodiments, the control and data acquisition system 42 derives one or more spectral yields associated with one or more elemental compositions (block 84) and estimates a measure of porosity (block 86) using one or more algorithms that utilize data associated with one or more environmental influences in the vicinity of the neutron induced gamma ray spectroscopy tool 54. In certain embodiments, the one or more environmental influences include a hydrogen index (HI) of the pore fluid, the HI of the formation matrix, the HI of the borehole fluid, formation lithology, formation salinity, borehole salinity, temperature, pressure, borehole size, tool spacing, invasion, or some combination thereof.

[0061] In addition, in certain embodiments, one or more algorithms are derived based at least in part on computer modeling, downhole log data, or some combination thereof. In addition, in certain embodiments, one or more algorithms are designed based at least in part on human judgment based on experience. In addition, in certain embodiments, one or more algorithms are based at least in part on machine learning, including but not limited to technologies such as multiple linear regression, neural networks, support vector machines, decision trees, extended neural network architectures that can include recurrent networks, long short-term memory (LSTM) networks, attention models, or integrated methods combining multiple instances of the aforementioned technologies.

[0062] Additionally, in certain embodiments, the method 80 may include generating neutrons of an energy spectrum that induces gamma rays via a radiochemical neutron source 62 of the neutron induced gamma ray spectroscopy logging tool 54. In other embodiments, the method 80 may include generating neutrons of an energy spectrum that induces gamma rays via a pulsed neutron generator 62 of the neutron induced gamma ray spectroscopy logging tool 54. Additionally, in certain embodiments, the one or more gamma ray detectors 64 of the neutron induced gamma ray spectroscopy logging tool 54 may include one or more scintillator detectors. Additionally, in certain embodiments, the one or more gamma ray detectors 64 of the neutron induced gamma ray spectroscopy logging tool 54 may include one or more solid-state detectors.

[0063] The technology presented and claimed herein is cited and applied to physical and specific examples of a practical nature that clearly improve the art, and therefore is not abstract, intangible, or purely theoretical. Further, if any claim appended at the end of this specification contains one or more elements that are designated as "means for [performing] [a certain function] ..." or "steps for [performing] [a certain function] ...", such elements are intended to be interpreted under 35 U.S.C. § 112(f). However, for any claim containing elements designated in any other manner, it is intended that such elements not be interpreted under 35 U.S.C. § 112(f).

[0064] The specific embodiments described above have been shown by way of example, and it should be understood that various modifications and alternative forms may be readily made to these embodiments. It should be further understood that the claims are not intended to be limited to the specific forms disclosed, but are intended to cover all modifications, equivalent forms, and alternatives that fall within the spirit and scope of the present disclosure.

Claims

1. A method comprising: receiving, via a control and data acquisition system, data related to an energy spectrum of gamma rays captured by one or more gamma ray detectors of a neutron induced gamma ray spectroscopy logging tool; deriving, via the control and data acquisition system, one or more spectral yields associated with one or more elemental components from the data associated with the energy spectrum of the gamma rays; as well as A measure of porosity is estimated via the control and data acquisition system based on the one or more spectral yields associated with the one or more elemental components.

2. The method of claim 1 , comprising deploying the neutron induced gamma ray spectroscopy logging tool into a borehole extending downhole through a geological formation via logging while drilling (LWD), cable, coiled tubing or other downhole conveyance mode.

3. The method of claim 1, wherein the one or more spectral yields associated with the one or more elemental components include one or more yields of the one or more gamma rays produced by capturing epithermal neutrons.

4. The method of claim 1, wherein the one or more spectral yields associated with the one or more elemental components include one or more yields associated with the capture of neutrons by hydrogen, the hydrogen being acquired by the one or more gamma ray detectors of the neutron induced gamma ray spectroscopy logging tool.

5. The method of claim 1, comprising inducing the energy spectrum of the gamma rays via an inelastic reaction of atomic nuclei with fast neutrons.

6. The method of claim 1, comprising inducing the energy spectrum of the gamma rays via radiative capture of neutrons by atomic nuclei.

7. The method of claim 1, wherein the one or more spectral yields associated with the one or more elemental components represent one or more relative fractions of the energy spectrum of the gamma rays associated with respective ones of the one or more elemental components.

8. The method of claim 1, wherein the one or more spectral yields associated with the one or more elemental components represent one or more absolute count rates of contributions of respective ones of the one or more elemental components to the total energy spectrum of the gamma rays.

9. The method of claim 1, wherein the control and data acquisition system derives the one or more spectral yields associated with the one or more elemental components and estimates the porosity measurement using one or more algorithms utilizing data associated with one or more environmental influences proximate to the neutron induced gamma ray spectroscopy logging tool.

10. The method of claim 9, wherein the one or more environmental influences include hydrogen index (HI) of pore fluid, HI of formation matrix, HI of drilling fluid, formation lithology, formation salinity, borehole salinity, temperature, pressure, borehole size, tool spacing, intrusion, or some combination thereof.

11. The method of claim 9, wherein the one or more algorithms are derived at least in part based on computer modeling, laboratory measurements, downhole logged data, or some combination thereof.

12. The method of claim 9, wherein the one or more algorithms are empirically designed based at least in part on human judgment.

13. The method of claim 9, wherein the one or more algorithms are based at least in part on machine learning.

14. The method of claim 1, comprising generating neutrons of the energy spectrum of the gamma rays via a radiochemical neutron source of the neutron induced gamma ray spectroscopy tool.

15. The method of claim 1, comprising generating neutrons of the energy spectrum of the gamma rays via a pulsed neutron generator of the neutron induced gamma ray spectroscopy tool.

16. The method of claim 1, wherein the one or more gamma ray detectors of the neutron induced gamma ray spectroscopy tool comprise one or more scintillator detectors or one or more solid state detectors.

17. A system comprising: Neutron induced gamma ray spectroscopy logging tool, which includes: a neutron source configured to generate neutrons to induce an energy spectrum of gamma rays; and one or more gamma ray detectors configured to detect the energy spectrum of the gamma rays; and A control and data acquisition system, the control and data acquisition system is configured to: receiving data related to the energy spectrum of the gamma rays captured by the one or more gamma ray detectors of the neutron induced gamma ray spectroscopy logging tool; deriving one or more spectral yields associated with one or more elemental components from said data associated with said energy spectrum of said gamma rays; and A measure of porosity is estimated based on the one or more spectral yields associated with the one or more elemental components.

18. The system of claim 17, wherein the one or more spectral yields associated with the one or more elemental components include one or more yields of the one or more gamma rays produced by capturing epithermal neutrons.

19. The system of claim 17, wherein the one or more spectral yields associated with the one or more elemental components include one or more yields associated with capture of the neutrons by hydrogen, the hydrogen being acquired by the one or more gamma ray detectors of the neutron induced gamma ray spectroscopy logging tool.

20. A control and data acquisition system comprising: one or more processors configured to execute instructions stored on a memory medium of the control and data acquisition system, wherein the instructions, when executed by the one or more processors, cause the control and data acquisition system to: receiving data related to an energy spectrum of gamma rays captured by one or more gamma ray detectors of a neutron induced gamma ray spectroscopy logging tool; deriving one or more spectral yields associated with one or more elemental components from said data associated with said energy spectrum of said gamma rays; as well as A measure of porosity is estimated based on the one or more spectral yields associated with the one or more elemental components.

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