Systems and methods for data processing in downhole operations

Abstract

A system (100; 100 ') for data processing in downhole operations. 600) and an associated method (500; 550) receiving a signal from a downhole environment using a downhole tool and using at least one processor that causes the system to determine (554) encoded data of the signal, where the encoded data is based in part on coefficients associated with at least one predetermined fit curve applied to data from different regions of the signal, and wherein the coefficients comprise (556) at least one difference between data of different regions of the signal and at least one predetermined fit curve. The system also converts the encoded data (504; 558) from the downhole environment (508; 562) to the terrestrial environment, and further determining (510; 510) the terrestrial environment based in part on decoding (564) the encoded data; 566) at least one parameter or level of an element in the downhole environment.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is a PCT application of U.S. non-provisional application No. 18 / 371,192, filed on September 21, 2023, entitled “SYSTEM AND METHOD FOR DATA HANDLING IN DOWNHOLE OPERATIONS”, which is related to and claims the benefit of priority to U.S. provisional application No. 63 / 408,506, filed on September 21, 2022, entitled “SYSTEM AND METHOD FOR DATA HANDLING IN DOWNHOLE OPERATIONS”, the entire disclosures of both applications being incorporated herein by reference for all intents and purposes. Background Art 1. Technical Field

[0004] The disclosure herein relates generally to equipment used in the natural gas industry, and particularly to data processing in downhole operations, such as logging while drilling operations.

[0005] 2. Description of the Prior Art

[0006] A wellbore is a structure formed in an underground or underwater geological structure or layer. Such an underground or underwater geological structure or layer contains pressure, which can be further enhanced by adding formation fluids (such as liquids, gases, or combinations) to the drill site or well site (such as a wellbore). Certain downhole operations, including logging while drilling (LWD) operations, may use one or more downhole tools with the ability to assess the elemental composition in the downhole environment. Such elemental composition or levels may include the content of potassium (K), uranium (U), and thorium (Th) (combined as KUTh) in the downhole environment. However, such downhole tools may need to communicate with surface equipment under limited bandwidth from the downhole environment. Summary of the invention

[0007] In at least one embodiment, a method for data processing in downhole operations is disclosed, the method comprising providing a downhole tool to receive a signal from a downhole environment, and comprising determining coded data for the signal. The coded data is based at least in part on coefficients associated with at least one predetermined fit curve applied to data from different regions of the signal. In addition, the coefficients include at least one difference between the data of the different regions of the signal and the at least one predetermined fit curve. The method also includes sending the coded data from the downhole environment to a surface environment, and determining at least one parameter or level of different elements in the downhole environment based in part on decoding the coded data.

[0008] In at least one embodiment, a system for data processing in downhole operations includes a downhole tool for receiving a signal from a downhole environment, a memory storing instructions, and a processor for executing instructions from the memory to cause the system to perform functions. The system determines coded data of the signal. The coded data is based at least in part on coefficients associated with at least one predetermined fit curve applied to data from different regions of the signal. The coefficients include at least one difference between the data of different regions of the signal and the at least one predetermined fit curve. Another function is to send the coded data from the downhole environment to the surface environment. The coded data includes at least one parameter or level of different elements in the downhole environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Various embodiments according to the present disclosure will be described with reference to the accompanying drawings, in which:

[0010] Figure 1 An example environment for a process subject to at least one embodiment herein is shown;

[0011] Figure 2 A graph illustrating conversion of channel numbers to energy levels for communications from a downhole environment and the graph is subject to the process of at least one embodiment herein;

[0012] Figure 3 A graph showing data associated with a signal and subject to encoding in at least one downhole tool of at least one embodiment herein;

[0013] Figure 4A Characterization of data associated with a signal of at least one embodiment herein is shown;

[0014] Figure 4B shows a data log that may be displayed in a user interface associated with data processing in downhole operations in at least one embodiment herein;

[0015] Figure 5A A method for data processing in downhole operations is shown in at least one embodiment;

[0016] Figure 5B Another method for data processing in downhole operations is shown in at least one embodiment; and

[0017] Figure 6 A system for data processing in downhole operations according to at least one embodiment is shown. DETAILED DESCRIPTION

[0018] In the following description, various embodiments will be described. For the purpose of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the embodiments. However, it will also be apparent to those skilled in the art that the embodiments may be practiced without the specific details. In addition, well-known features may be omitted or simplified to avoid obscuring the described embodiments. Various other functions may be implemented within the various embodiments, as well as discussed and suggested elsewhere herein.

[0019] In at least one embodiment, the systems and methods herein can address such deficiencies presented and pointed out throughout the present invention by including a downhole tool having one or more subsystems for handling data communications. A spectral gamma ray (SGR) data communications system includes a processor that can communicate using a 512 or 256 channel data spectrum. For example, such an SGR communications system can be semi-automatic and support complex data communications, but may not support current LWD aspects.

[0020] In at least one embodiment, the SGR communication system may not work with a downhole tool because of at least the amount of data to be sent and because of the environmental corrections required for energy channels or windows that represent regions of interest for signals to be sent to the downhole environment at the surface. Regions of signals may be required to determine levels (such as occurrences) of elemental content (such as for KUTh content in the downhole environment). In addition, there is limited bandwidth available for downhole tools to support round-trip communications in LWD operations. In at least one embodiment, such limited bandwidth may be about 3 bits / second. In an alternative embodiment, such limited bandwidth may be about 10 bits / second.

[0021] In at least one embodiment, although the windowed data set of several total energy windows (such as 3, 9 or 16 energy windows) can be compiled to be sent as windowed data, such a process still generates higher data points, requiring about 32 bits per data point to be sent from the downhole environment. This method consumes or occupies at least the available bandwidth for an extended period of time, and may require that the downhole tool be maintained at each depth position for a longer period than expected. In at least one embodiment, such communications are provided from the downhole environment to the process at the surface environment via mud pulse telemetry (MPT), acoustic telemetry or electromagnetic telemetry.

[0022] In at least one embodiment, data communication herein may entail transmitting a collection of natural gamma ray signals having an energy spectrum such as in an energy range from 60 kiloelectronvolts (keV) to 2400keV in 512 energy channels. Such gamma ray signals can be used to identify contributions to the energy window from different elements such as potassium (K), thorium (Th), and uranium (U). For example, a 3-component inversion (for the KUTh element) can be used with environmental correction (to account for application errors from application fluids that are not part of the downhole environment but can be used in drilling operations, or from natural errors caused by wellbore size). In at least one embodiment, such application fluids can be application muds.

[0023] In at least one embodiment, to address such shortcomings, the systems and methods herein process data by compressing energy window data using an encoding process that combines function transform prefitting and differential encoding. In addition, for signals such as energy spectrum gamma ray signals, logarithmic data such as counts or count rates of gamma radiation can be used. In at least one embodiment, the systems and methods herein enable compression to send data collected from a downhole environment in near real time as part of the data processing operations discussed herein, which allows data on elemental composition to be realized in near real time.

[0024] In at least one embodiment, the systems and methods herein reduce the data of 512 channels to N energy windows. The channels forming the energy windows define the breadth (or width) of the energy windows associated with the known energy range of the elements (such as KUTh elements). In at least one embodiment, the N channels can be nine channels. In at least one embodiment, the breadth can be defined by three to twenty data points constituting the data, at least according to a transformation function, such as a logarithmic transformation of the collected energy values ​​applied within the collected energy windows. In at least one embodiment, three to twenty data points can be multiple energy windows constituting the data to be compressed. In addition, the energy window can be the sum of any subset of the channels. In at least one embodiment, the sum of channels 1-100 can be the first energy window, the sum of channels 101-150 can be the second energy window, and so on.

[0025] In at least one embodiment, the logarithmic transformation is part of the encoding applied to the collected data. Such encoding is performed in a downhole environment using at least one processor or encoder that is part of a downhole tool and is associated with a memory having instructions that allow such at least one processor or encoder to perform the functions described throughout this document. In at least one embodiment, at least one processor or decoder in the surface environment can be used to decode the encoded data from the downhole tool.

[0026] In at least one embodiment, an inverse transform function (such as an inverse logarithmic transform) may be applied as part of the decoding of the encoded data. In addition, in at least one embodiment, a relative error level (such as 10%) may be used in the decoding step of the ground environment to account for the application errors described herein. Such a 10% error may be the result of lossy encoding between the input data and the decoded data. For example, such percentage error information may be a prerequisite to allow for a determined elemental content or composition (such as from the KUTh element) of the decoded data with sufficient accuracy.

[0027] In at least one embodiment, Figure 1 An example environment is shown that is subject to the procedures described herein. Figure 1 Schematic diagram of an embodiment of a logging while drilling (LWD) system 100 according to at least one embodiment herein. The LWD system 100 may include a rig 102 and a drill string 104 coupled to the rig 102. However, other implementations of the LWD system may incorporate features of the methods and systems disclosed herein. The drill string 104 includes a drill bit 106 at a distal end that may be rotated to engage a subsurface or surface formation 108 and form a wellbore 110.

[0028] The drill string 104 may be formed of one or more pipes mechanically coupled together, such as via threads, specialized couplings, etc. As shown, the wellbore 110 includes a wellbore sidewall 112 and an annulus 114 between the wellbore 110 and the drill string 104. In addition, a bottom hole assembly (BHA) 116 may be positioned at the end of the drill string 104. In the example shown, the BHA 116 may be positioned at the bottom of the wellbore 110. The BHA 116 may include a drill collar 118, a stabilizer 120, etc.

[0029] In at least one embodiment, the LWD system 100 includes various tools 122, such as logging tools and surface logging tools, which can be used to obtain measurements from the formation 108. Logging tools that are part of the BHA include, for example, logging while drilling tools as described herein and downhole tools, which may include nuclear tools, sonic tools, seismic tools, magnetic resonance tools, resistivity tools, sampling tools, etc.

[0030] In addition, at least one embodiment of the present invention may be provided. Figure 6 Computational aspects are discussed to enable data processing in downhole operations. Figure 6 Aspects of the invention may be located above ground in a surface environment and partially located in a downhole tool of the LWD system 100 that is in the downhole environment but can communicate with the surface environment outside the wellbore. When located above ground, Figure 6 These aspects of the present invention may be performed at a drill or well site, or may be performed at a remote facility other than a drill or well site.

[0031] Although the LWD system 100 is described in part, at least one embodiment herein may be used in measurement while drilling (MWD) or logging while drilling (LWD) operations. In addition, at least one embodiment herein may be used in wireline implementations, coiled tubing implementations, or wellbore operations that may incorporate resistivity logging techniques, all of which may benefit from the present data processing features.

[0032] In at least one embodiment, a sensor assembly (such as a detector / receiver) may be configured to be transmitted downhole on a wireline. This allows data from the downhole environment to be recorded on an appropriate memory device, processed (such as encoded), and transmitted or retrieved for subsequent processing in real time or near real time. A downhole tool as described herein and having such a sensor assembly may include a crystal scintillator and a photomultiplier tube as part of the sensor assembly, and may include an encoder (or a processor with an encoder). In addition, a transmitter is provided for transmitting data processed by the downhole tool to a surface environment outside the wellbore.

[0033] Figure 2 A graph 200 of the conversion of channel numbers to energy levels is shown. For example, the channels shown in the graph 200 are configured to collect count data from natural gamma ray (GR) signals in a downhole environment. In at least one embodiment, the energy levels include energy ranges, such as from 60keV to 2800keV in 512 energy channels 202. In at least one embodiment, since the detector can be an interacting crystal and a photomultiplier tube, it is necessary to convert the energy levels to channel numbers to measure the count rate (within the energy window) of the collision radiation energy. The conversion of energy levels to channel numbers can also be referred to as calibration of the detector.

[0034] In at least one embodiment, graph 200 shows two conversions of energy levels to channels 204, 206. The two conversions may coincide at the higher energy channel 208. To address bandwidth limitations, only the range of channel numbers associated with gamma radiation from the element in question may be selected. However, more channels for identifying the presence of radioactive elements in a downhole environment may facilitate better resolution (such as higher resolution) of grouped signals or data corresponding to the elements.

[0035] exist Figure 2In the example of , the channel number 208 corresponding to the energy range of the KUTh element is known on the receiving side (such as at the surface environment). In at least one embodiment, similarly, only data points (associated with certain channels) or energy windows for those ranges need to be provided, and the system in the surface environment receives such data points for consecutive channel numbers. Therefore, in such a process, it may not be important to identify data points beyond those data points. However, in at least one example, each data point is represented by 32 bits, which is time consuming for a 3 bit / second bandwidth. In addition, such element detection may be required at multiple depth locations, thus requiring the downhole tool to move within a predetermined time or at a predetermined penetration rate (depth interval per time unit), and data communication may not be real-time or may cause delays in such detection requirements.

[0036] Figure 3 A graph 300 of data associated with a signal and limited to data encoded in at least one downhole tool of at least one embodiment of the present invention is shown. Such a signal may be used interchangeably with a GR signal herein. The signal may originate from a gamma emitting element in a downhole environment. The gamma emitting element may be located in a downhole formation 108 ( Figure 1 ), in the borehole fluid, or in a radioactive tracer placed in the formation or borehole wall. The signal can form or define a signal curve. Figure 3 In the figure, the signal curve shows the relationship between the gamma count rate and the energy. In addition, Figure 3 A relationship between gamma count measurements (such as counts 302) and energy (MeV) 304 is provided, on which data encoding herein may be relied upon. In addition, for each channel, a separate count rate may be determined. The count rate is associated with the channel and is within an energy window 312. The vertical lines indicate the boundaries of the energy window. The energy window is based on Figure 2 Each energy window combines a certain number of energy channels 208. The energy channels ( Figure 2 ) can be summed to provide a total count rate for the energy window.

[0037] In at least one embodiment, for KUTh element detection and measurement, the radioactive element 40 K. 238 U and 232 The specific isotopes of the Th decay chain may be correlated and thus may be extracted from the GR spectrum of the GR signal (radiation). In at least one embodiment, the ratio of the gamma counts of the GR signal may be measured. These counts relate to a portion of the Compton region (or Compton window) and a portion from the photoelectric region (or photoelectric window or photopeak region) of the gamma ray spectrum.

[0038] In at least one embodiment, it is desirable to select an energy window 312 that falls within the entire range (i.e., weak detection to strong detection and back to weak detection for each element). In at least one embodiment, the GR signal for three example elements (K, U, Th) as measured from actual rock samples may be between 1.15 MeV and 2.8 MeV 304 of the GR signal spectrum, which corresponds to a portion of the Compton window.

[0039] In at least one embodiment, Figure 3 A graph 300 of data specifically in three sections 306, 308, 310 is shown. These sections are associated with the KUTh element or at least one parameter associated with an element of the downhole environment. In at least one embodiment, a second energy window (i.e., a photoelectric window) can be used to provide additional information about different isotopes of the KUTh element. For example, in all such windows 312, compression for data processing discussed with reference to at least the Compton window can be performed.

[0040] In at least one embodiment, instead of a natural GR signal, at least one parameter associated with an element of the downhole environment involves information from a pulsed neutron source in a downhole tool that is used together with neutron induced gamma radiation or spectroscopy in the downhole environment. Neutron induced gamma spectroscopy includes neutron generation and gamma spectroscopy. In pulsed mode, a separate gamma spectrum can be acquired from a neutron pulse. In at least one embodiment, the neutron radiation intensity can be associated with the duty cycle and frequency of the neutron generator. These aspects can be different between the pulsed mode and the continuous mode available in neutron induced gamma spectroscopy. In at least one embodiment, the use of neutron induced gamma spectroscopy means that the signal from the downhole environment is a return signal (induced or scattered radiation) that is acquired and encoded throughout the compression method described herein.

[0041] A background or portion of the gamma spectrum from downhole ambient radiation can be acquired. In at least one embodiment, a gamma detector can be used for such acquisition. Then, the results of neutron induced gamma spectroscopy measurements performed in continuous mode (DC) or pulsed mode (INS) can be determined. Certain peak areas and standard deviations can be determined to provide information from the return signal. For neutron induced gamma spectroscopy data, the region of interest can be the number of counts from neutron induced gamma spectroscopy at a specific energy, which is attributed to a specific element contributing to a specific peak area. Then, as referenced to at least one predetermined fit curve, the normalized peaks or areas in the neutron induced gamma spectroscopy can be used together with the errors therein to provide compressed or encoded data back to surface equipment.

[0042] Thus, in at least one embodiment, a method for data processing in downhole operations includes data processing of return signals from neutron induced gamma spectroscopy in a downhole environment. In at least one embodiment, this method includes providing a downhole tool to receive return signals from neutron induced gamma spectroscopy in a downhole environment. Additional steps in this method include determining coded data of normalized peaks or areas in the return signal. The coded data is based in part on coefficients associated with a transform function of data applied to different peaks of the return signal.

[0043] In at least one embodiment, the coefficients of the fitted curve may include at least one error between data of different peaks of the return signal and at least one predetermined fitted curve. In at least one embodiment, the method includes sending the encoded data from the downhole environment to the surface environment. In addition, the method includes determining at least one parameter or level (occurrence) of different elements in the downhole environment based in part on decoding the encoded data.

[0044] In at least one embodiment, a method for data processing in downhole operations includes providing a Figure 1 and Figure 6 300 , to receive a signal (such as a GR signal or a return signal neutron induced gamma spectroscopy) from the downhole environment. In one example, the signal may be a return signal that is related to an application signal from the downhole tool applied to the downhole environment. The graph 300 base data may be retrieved from such a signal in the downhole tool. In at least one embodiment, even in Figure 3 The underlying data from the signal can be used alone by the systems and methods described herein, as shown in the graph 300 in FIG. 1. In at least one embodiment, for example, a crystal scintillator and a photomultiplier tube can be coupled to a processor and instructions from a memory can be executed to determine count information at a selected Compton window of the data.

[0045] In at least one embodiment, the Compton window can be further divided into allocated energy windows 312. Such allocated energy windows can be a division of the energy scale 304 into three to twenty data points. In at least one embodiment, the number of energy windows can be predetermined using at least one rock sample tested for gamma ray signals. In at least one embodiment, such predetermined number of energy windows can be between three and twenty energy windows.

[0046] In at least one embodiment, some of these energy windows 312 may cover a portion of the Compton window of the entire energy range of radiation having the KUTh element, as shown. Such energy windows 312 may be predetermined and associated with the energy levels 304 of the received counts 302. In addition, the number of points of individual energy windows in different energy windows may be based at least in part on the width of the individual energy windows in different energy windows. In addition, for energy windows of wider width, there may be a higher number of points or data points (counts in the associated channel) that may be assigned to the energy window.

[0047] In at least one embodiment, the processor may use such energy windows 312 in part to determine the encoded data of the signal. In a first step, the count or count rate 302 values ​​of the data points in each energy window 312 are summed or averaged for the corresponding energy window 312 to provide a corresponding energy window average count or count rate (EWavg). That is, the counts associated in the energy channels combined into the energy window are summed to provide the count or count rate of the corresponding energy window. In at least one embodiment, EWavg is normalized and then logarithmically transformed.

[0048] In at least one embodiment, the logarithmic transform is a base 2 logarithmic transform. Logarithmic transform (EWavg) is a transform function that represents this step. In addition, as part of the encoding process, the value from the logarithmic transform (EWavg) function can then be related to the number of energy bins 312 from which the value is summed or averaged. In at least one embodiment, while the logarithmic method herein is one method of transform function, other suitable transform functions that can be applied to generate the coefficients herein include arctangent, square root, arccosine, exponential power, and other obvious functions based in part on the description herein.

[0049] Figure 4A Features 400 of encoded data associated with a signal of at least one embodiment of the present invention are shown. Features 400 relate to SGR energy window compression 402 using energy windows 406 and counts or counts per second 404 (count rate) associated with a transformation function that is a logarithmic transformation function. For example, a logarithmic transformation (EWavg) on ​​the y-axis (referred to as normalized counts per second 404) includes data points 414 that are plotted to the number of energy windows 406 on the x-axis to form a transformed input curve (transformed signal curve). The signal curve includes multiple count rates in multiple energy windows.

[0050] In at least one embodiment, the feature 400 includes an input curve 412, which is an input that is subjected to data processing (such as for compression described throughout this article). The input curve can be a signal curve formed from the signals (counts or count rates) received in the energy window 406. In at least one embodiment, the instructions in the memory associated with the processor may include one or more predetermined fitting curves 410, which are regression curves. For example, a logarithmic regression curve can be used as a predetermined fitting curve 410 to fit the input curve 412 between the logarithmic transformation (EWavg) and the energy window 406. In at least one embodiment, such a predetermined fitting curve 410 can be a straight line and have different slopes and intercepts to try to find the best fit.

[0051] In at least one embodiment, the processor can determine the error 416 (or logarithmic difference 418) between the logarithmic transformed (EWavg) value and the corresponding y-axis value of one or more predetermined fitting curves 410 at each number 406 of the energy window. The error 416 can be the actual difference 418 between each logarithmic transformed (EWavg) value (the transformed input curve) and each corresponding y-axis value of the predetermined fitting curve, or can be a normalized or scaled version of the logarithmic difference to fit between predetermined thresholds, such as -1 to 1 (labeled as logarithmic error or difference 408 for illustrative purposes). In addition, the error can be a difference as a scaled value (such as a 3-bit value in the range of + / - [0, 0.8]); however, larger differences (such as 1.2) can be scaled to these values ​​(such as to 0.8). In one embodiment, the scaling value (variable number of bits) can be selected to represent the entire range of logarithmic differences, or the fitting curve can be selected to produce a difference that can be represented by the scaling value (fixed number of bits). Thus, the variable number of bits depends on a predetermined error, and the predetermined error may be related to a difference between the signal curve and a decoded signal curve generated from the decoded data.

[0052] Thus, in at least one embodiment, at least one predetermined fit curve may be selected from a number of predetermined fit curves based at least in part on ensuring that at least one error is within a predetermined threshold. The methods herein attempt to use an available scaled set of coefficients (such as slope and intercept) to ensure a best fit. However, for exemplary reasons, when the best fit will be achieved for the value 6.6567, but where the available points are part of a scaled 3-bit coefficient, then such a transmission may include only one decimal point, such as […, 6.3, 6.5, 6.7…]. Thus, for this example, 6.7 may be selected for the fit curve. Furthermore, the predetermined threshold may therefore be related to the limitations of the transmission.

[0053] In at least one embodiment, at least one predetermined fit curve can be selected from a plurality of predetermined fit curves based at least in part on the statistical significance of the error within a predetermined threshold. In at least one embodiment, this method allows scaling of coefficients associated with a transform function. Scaling values ​​with a predetermined range of intercept and slope can be obtained. For example, an intercept range such as [5,9] at 3 bits and a slope range of [0,0.8] at 3 bits can be used as part of the scaling value.

[0054] In at least one embodiment, for each number 406 of energy windows, all or at least 90% of the errors between the logarithmic transformation (EWavg) value and the corresponding y-axis value of the predetermined fitting curve may be within -1 to 1. However, in at least one embodiment, the error percentage may be a predetermined threshold and may be based in part on predetermined ranges and scaling parameters that are programmed into the downhole tool prior to deployment to perform data processing in downhole operations. These parameters may be changed during operation. For example, the tool and telemetry rates may be programmed and reprogrammed by the downlink; the transformation function may be changed; and the fitting curve may be changed, and the coefficients or predetermined error thresholds may be changed accordingly.

[0055] In at least one embodiment, such selection of a predetermined fit curve represents performing a curve fit between logarithmic data (such as counts or count rates) of different energy windows of the signal and a number of predetermined fit curves with different slopes and different intercepts stored in a memory (such as a lookup table) of the downhole tool. Thus, in at least one embodiment, the selection of at least one predetermined fit curve from a plurality of predetermined fit curves may be based at least in part on the statistical significance of at least one error being within a predetermined threshold. This allows for incorporation of the best approximation to enable reconstruction of data from decoding the encoded data.

[0056] For example, the requirement may be to determine at least one of a plurality of predetermined fit curves having associated errors with respect to input data of different energy windows, i.e., the minimum number of errors of the plurality of predetermined fit curves. When such a determination is made, where at least one of the predetermined fit curves has all associated errors (differences) representing the least number of error percentages (such as 5% of the input data 412 and the predetermined fit curve 410 indicating error 418), the downhole tool herein, through its processor, is able to select the predetermined fit curve for encoding data of different energy windows.

[0057] In at least one embodiment, this fitting process allows the encoded data to be based in part on the coefficients of the transformation function. The coefficients may include the slope and intercept of a predetermined fitting curve. The encoded data includes the coefficients and at least one difference indicator indicating the value of the error or difference between data (such as logarithmic data) of different energy windows of the signal in the input data (signal curve) and a point on at least one predetermined fitting curve. The fit may be represented by the following equation (1).

[0058] log2-regressiony′=α*(EnergyWindowNumber-1)+b......Equation (1)

[0059] Equation (1) can be generalized according to equation (2):

[0060]

[0061] In equation (2), relative to equation (1), a = w1 and b = w0 and N = 1. In at least one embodiment, the slope a and the intercept b represent stored coefficients (slope and intercept) of a predetermined fit curve, which can be selected so that each point on the predetermined fit curve is within a predetermined threshold or difference (representing error) from the input data represented by the logarithmic transformation (EWavg) value from the gamma ray signal.

[0062] In at least one embodiment, the encoding includes a scaled logarithmic error or difference 408 given by equation (3).

[0063] Δ=y-y'…………Equation (3)

[0064] As described elsewhere herein, y represents at least the y-axis logarithmic transformation (EWavg) value from the gamma-ray signal, and therefore, there is an error or logarithmic difference between y and y', where y' is from equation (1) or (2).

[0065] In at least one embodiment, the coded data is a compilation of a slope contributing a 3-bit value to the coded data, an intercept contributing a 3-bit value to the coded data, and at least one difference indicator contributing a 4-bit value to the coded data. In at least one embodiment, each of such bit sizes is only exemplary and more or less bits may be used to represent such coded data. 4 bits may include a 3-bit value and a 1-bit sign value (indicating a positive or negative error). The coded data is a digital representation of the input data (signal curve) 412.

[0066] Thus, in at least one embodiment, a total of 10 bits is sufficient to communicate the presence of an element of the downhole environment (such as a KUTh element) of one energy window numbered 406 to the surface environment. In addition, the encoded data includes sending less than 10 bits per second to the surface environment. Thus, in at least one embodiment, the encoded data to be sent for all such energy windows is a [3 bits], b [3 bits], Δ 1-N [9×4=36 bits], which represents a total of 42 bits of comparison reference for all data points of the KUTh element across all energy windows Figure 3 The 32 bits required for each data point (unencoded) of the features in .

[0067] Figure 4A Decoded data such as a decoded input curve (decoded signal curve) (thinner dashed line 420) is also shown to be nearly coincident with the input curve 412. In at least one embodiment, once the encoded data is sent from the downhole environment and received at the surface environment outside the wellbore, the levels (occurrences) of elements such as potassium, uranium, and thorium in the downhole environment can be determined based in part on decoding the encoded data. In at least one embodiment, such decoding can include generating representative data using the slope, intercept, and at least one error (difference) from the encoded data as part of decoding at the surface environment. In at least one embodiment, a portion of such decoded data using the slope, intercept, and at least one error is shown as the thinner dashed line 420. Therefore, the decoded data is faithful to the logarithmic transformed (EWavg) value (input data or signal curve) before encoding. In at least one embodiment, aspects of the decoding can be represented by the following equation (4).

[0068] y″=y′+Δ…………Equation (4)

[0069] In one embodiment, the encoding may be performed with a predetermined number of bits, such as 3 bits for each coefficient (slope, intercept) of the fitted curve and 4 bits for each difference indicator, resulting in 42 bits for a signal curve including nine difference indicators in nine energy windows. In one embodiment, the number of bits used to encode the signal curve may be variable and may be optimized to have a decoded signal curve error within a predetermined threshold. The decoded signal curve error is caused by using scaled values ​​of the coefficients and difference indicators for the encoded data. Figure 4A The decoded signal curve error in is the difference between the input data (signal curve) and the decoded data (decoded signal curve). Achieving an error within a predetermined threshold (e.g., up to 1% or up to 5%) may require a finer scaling of the scaling values ​​of the coefficients and / or the difference indicator. A finer scaling may require a larger number of bits to encode the coefficients and / or the difference indicator.

[0070] In at least one embodiment, an inverse transformation function (such as an inverse logarithmic function) may be performed on the representative logarithmic data of the decoded signal curve to generate count data (inverse transformed decoded signal curve) for different energy windows. For example, the number of data points in the allocated energy window 312 is known according to the encoding algorithm. Therefore, in at least one embodiment, once representative logarithmic values ​​that are mostly faithful to the logarithmic transformation (EWavg) values ​​are determined by the inverse logarithmic function, they can be adjusted to the number of data points to reconstruct the Compton window 312 to achieve the levels of at least potassium, uranium, and thorium in the downhole environment.

[0071] In at least one embodiment, the count of a window can always be a superposition of multiple elements. Therefore, the methods herein will be considered approximate. Alternatively, although inversion modeling such as linear inversion or matrix inversion y=A*kuth can be performed, where A includes end member curves (100%) of various elements (such as K, U, Th elements), the present method is able to compress the data while also providing comparable communication of the element content or at least one parameter from the downhole environment.

[0072] In addition, this method can also be applied to data that exhibits trends, such as data that decays or grows exponentially or otherwise, where such data is transmitted between a downhole tool and surface equipment. In at least one embodiment, the signal can be a gamma radiation (GR) signal, an optical signal, or other electromagnetic waves or radiation. In at least one embodiment, using GR for the signal, the counts or counts per second associated with the GR signal can be recorded for compression and communication herein. In at least one embodiment, the method herein is applicable to transmitting any downhole data that exhibits rising and falling trends, including using signals such as acoustic signals, pressure-based signals, flow rate-based signals, or resistivity-based signals. In at least one embodiment, for applications that include energy windows (such as Figure 4A As described in , data point numbers can be used instead. Thus, the data points can be on the x-axis and measurements of signal components reflecting elemental composition or data trends (such as pressure, flow rate, etc.) can be on the y-axis without the need for logarithmic transformation.

[0073] In downhole applications, gamma spectra are detected at different borehole depths, such as in wireline logging applications or in logging while drilling applications. Figure 4A ) performs the method described in the present application, the plurality of input data such as a plurality of signal curves corresponding to gamma energy spectra received at different wellbore depths. Figure 4AThe input data provided in can be received at the detectors at multiple depth values ​​along the wellbore. The encoding and transmission of data from the downhole environment to the surface environment can be performed in real time while drilling, and multiple encoded data are provided for the input data received at the detectors at multiple depth values.

[0074] Each of the plurality of coded data may be associated with a depth value. The decoded data associated with the transmitted plurality of coded data may be used to perform wellbore operations, such as generating a data log (signal curve (gamma spectrum) versus depth) at a surface environment outside the wellbore in real time while drilling, changing operating parameters (such as drilling parameters), and adjusting the drilling trajectory in real time.

[0075] Figure 4B A data log 450 that can be displayed in a user interface associated with data processing in a downhole operation is shown. The data log 450 shows information of occurrences of KUTh elements in a downhole environment versus borehole depth (e.g., measured depth (MD) from 3050 feet to 3125 feet in the highest depth interval). In the left track 452 of the data log 450, bulk information 454 of the occurrences of gamma emitting elements (KUTh) is displayed. The bulk information of the occurrences in the left track is provided in API units (American Petroleum Institute) from 0 API on the left to 150 API on the right. The bulk information of the occurrences relates to the occurrences of gamma emitting elements (such as KUTh elements) that emit gamma in the downhole environment in the detected energy range. The solid line (with jitter) in the left track represents the bulk information of the occurrences associated with different depths 458 (in feet) on the y-axis measured downhole and stored to the downhole tool memory (also referred to herein as "spectral GR-bulk-memory").

[0076] Jitter in the memory data may be related to noise or environmental influences. In addition to the data from the memory ("Spectrum GR-Large Capacity-Memory"), data from real time (large batches of information that appear) can be displayed in the same data log 450. The data from real time comes from encoding the gamma spectrum recorded at the downhole environment at each depth position, which is then provided as encoded data that is sent to the surface environment and decoded. This is in Figure 4B 45, within the same depth graph 458, but shown as a dashed line without jitter to represent "Spectrum-GR-Bulk, Real-Time (Encode-Decode)". As can be seen in the left track, there is good agreement between the information from the memory and the information decoded at the surface environment, which demonstrates the power of the compression method as described herein.

[0077] Thus, in at least one embodiment, the system herein receives a first signal at a first borehole depth defining a first signal curve, and receives a second signal at a second borehole depth defining a second signal curve. In at least one embodiment, the memory data represents data downloaded from the downhole tool after the drilling operation is terminated and when the downhole tool returns to the surface environment. Figure 4B As shown in , this memory data may be plotted in a data log 450 for illustrative purposes, such as for demonstrating the performance of the encoding method. The left track 452 in the data log shows that the encoded data sent to the surface environment allows for efficient representation of the spectral GR-bulk data as recorded in the downhole environment.

[0078] In at least one embodiment, three additional tracks 462-466 ​​are provided to the right of the first track 452 and show different spectral components 468 of the gamma spectrum, such as potassium (K), uranium (U), and thorium (Th) in the same y-axis 458 (depth). The x-axis 456 represents the information present in units of percentage or parts per million (ppm). Although the memory data may be recorded downhole and downloaded from the downhole tool memory, this is shown side by side with the real-time data, which is decoded at the surface environment from the transmitted encoded data, shown in dashed lines, while the memory data is shown in solid lines (with jitter).

[0079] To achieve the spectral contribution of potassium, uranium, and thorium, the decoded data (such as decoded signal curves) may be subjected to inversion modeling, as previously described in this specification. Based on the spectral GR information, the occurrence of potassium, uranium, and thorium in the downhole environment may be determined for different depths along the wellbore, thereby allowing identification of specific downhole environmental rock formations or allowing lithology to be mapped, such as identifying clay minerals at depth and shown in the data log 450. All data shown in the data log 450 (wellbore size, mud composition, etc.) may be corrected for environmental effects on the data. The data log 450 displays bulk information and spectral information at three different depth intervals, such as between 3050 feet and 3125 feet, between 3275 feet and 3350 feet, and between 3800 feet and 3875 feet.

[0080] Figure 5A A method 500 for data processing in downhole operations in at least one embodiment is shown. Figures 3 to 4BAs discussed, the method 500 includes providing 502 a downhole tool to receive a signal from a downhole environment. A further step is performed in the method 500 for determining 504 coded data for the signal. The coded data is based at least in part on coefficients associated with at least one predetermined fit curve applied to data from different regions of the signal. In addition, the coefficients include at least one difference between the data of the different regions of the signal and the at least one predetermined fit curve. For example, the coded data may be based in part on a slope, an intercept, and at least one error or logarithmic difference, the logarithmic difference being a base 2 logarithmic difference between the logarithmic data of different energy windows of the signal and the at least one predetermined fit curve.

[0081] In at least one embodiment, the method 500 includes determining or verifying 506 that the coded data is ready to be sent, such as by checking that a bit register is full. In at least one embodiment, the method 500 includes sending 508 the coded data from the downhole environment to the surface environment. In at least one embodiment, the method 500 includes determining 510 at least one parameter or level of different elements in the downhole environment based in part on decoding the coded data. At least one parameter in the downhole environment includes the presence of at least one radioactive element in the downhole environment. For example, the levels of at least potassium, uranium, and thorium in the downhole environment can be determined based in part on decoding the coded data.

[0082] Figure 5B Another method 550 for data processing in downhole operations is shown in at least one embodiment. The method 550 can be used with Figure 5A The method 500 in the embodiment of the present invention may be performed together with Figure 5A The method 500 is executed separately. Figure 5B The method 550 in the embodiment includes providing 552 a downhole tool to receive signals from a downhole environment within a wellbore. The signals define a signal curve. For example, the method 550 includes receiving a first signal at a first wellbore depth defining a first signal curve, and receiving a second signal at a second wellbore depth defining a second signal curve.

[0083] The method 550 includes determining 554 coefficients of a fitted curve that fits the signal curve (where, for example, a first signal curve is detected at a first depth and / or a second signal curve is detected at a second signal curve). The method includes determining 556 a difference indicator representing a difference between the signal curve and the fitted curve. The method includes encoding 558 the coefficients and the difference indicator to provide encoded data representing the signal curve. A verification 560 that the encoded data is ready to be sent may be performed. For example, the encoded data is filled into a buffer and indicates the verification 560 performed. The method 550 includes sending 562 the encoded data from the downhole environment to a surface environment outside the wellbore. The method 550 includes receiving and decoding 564 the encoded data at the surface environment to provide decoded data. The method 550 includes determining 566 at least one parameter of the downhole environment based in part on the decoded data. In one embodiment, the verification step 560 may be omitted.

[0084] In at least one embodiment, the signal curve has multiple count rates in multiple energy windows. In addition, as part of step 566, at least one parameter in the downhole environment can include the presence of at least one radioactive element in the downhole environment. Method 550 includes steps or sub-steps for providing a pulsed neutron source in the downhole tool. The pulsed neutron source is associated with neutron-induced gamma radiation in the downhole environment. In addition, the signal received from the downhole environment is related to neutron-induced gamma radiation. Method 550 supports that at least one radioactive element in the downhole environment includes one of potassium, uranium, or thorium.

[0085] The method 550 includes a step or sub-step of generating a decoded signal curve using the decoded data as part of decoding at the surface environment. An additional step or sub-step is for performing inversion modeling based on the decoded signal curve to determine the occurrence of at least one radioactive element in the downhole environment. In addition, the method 550 includes a step or sub-step for subjecting the signal curve to a transformation function to provide a transformed signal curve. Then, a step for determining a fitting curve based on the transformed signal curve can be performed.

[0086] In method 550, the transformation function is one of a log2 function, an inverse tangent transformation function, a square root transformation function, or an exponential power transformation function. In addition, the coefficients may include a slope and an intercept, and the signal curve may include count rates in at least five energy windows. Method 550 causes the encoded data to include a predetermined number of bits or may include a variable number of bits. The variable number of bits depends on a predetermined error. The predetermined error may be related to the difference between the signal curve and the decoded signal curve generated from the decoded data.

[0087] In at least one embodiment, the signal from the downhole environment is from a wellbore operation including one of log generation or change of an operating parameter. In addition, the step of transmitting 562 the encoded data includes transmitting less than 10 bits or less than 5 bits per second to the surface environment. In addition, the transmitting 562 of the encoded data may include using one of mud pulse telemetry, acoustic telemetry, or electromagnetic telemetry. In at least one embodiment, the method 550 includes using a fitting curve that is a predetermined fitting curve and includes coefficients stored in a memory in the downhole tool.

[0088] Figure 6 A system 600 for data processing in downhole operations according to at least one embodiment is shown. The system 600 may include computer and network aspects. In at least one embodiment, these computer and network aspects 600 may include a distributed system. In at least one embodiment, the distributed system 600 may include one or more computing devices 612, 614. In at least one embodiment, the one or more computing devices 612, 614 may be adapted to execute and function with client applications (such as browsers or stand-alone applications), and are adapted to execute and function on one or more networks 606, which may include downhole tool-to-tool communications and telemetry to the surface (such as using mud pulse telemetry, acoustic telemetry, electromagnetic telemetry), where a receiver on the surface (e.g., a pressure transducer or antenna) is capable of telemetry acquisition.

[0089] In at least one embodiment, a server 604 having components 604A-N may be communicatively coupled to computing devices 612, 614 via a network 606 and via a receiver device or detector 608 (if provided). In at least one embodiment, the components 612, 614 include a processor, memory, and random access memory (RAM). In at least one embodiment, the server 604 may be adapted to operate a service or application to manage functions and sessions associated with database access 602 and associated with the computing devices 612, 614. In at least one embodiment, the server 604 may be associated with a detector 608 of a downhole tool 620, wherein such a detector may include a crystal scintillator. In at least one embodiment, a photomultiplier tube 618 may be associated with the downhole tool 620.

[0090] In at least one embodiment, the encoder and transmitter 616 can be associated with a photomultiplier tube 618. In at least one embodiment, the encoder and transmitter 616 can include a processor and a memory having instructions that, when executed by the processor, can cause the encoder and transmitter 616 to perform the functions described herein and at least with reference to Figure 3 , the encoding functions described in Figures 4 and 5.

[0091] In at least one embodiment, the server 604 can be located at the wellsite location, but can also be located at a location different from the wellsite location to perform the functions described throughout this document and at least with reference to Figure 4A or Figure 4B In at least one embodiment, such a server 604 can support data processing in a downhole tool 620 operating downhole in a downhole environment 622. Such a tool 620 can be located partially downhole and partially operated in a surface environment. Such a tool 620 can include subsystems that perform the functions described throughout this document.

[0092] For example, the subsystem may be a module capable of testing or training the system at the surface level using a predetermined fit curve as an activation function. The subsystem may be encapsulated in one or more computing devices having at least one processor and a memory such that the at least one processor may perform functions based in part on instructions executed in the at least one processor from the memory. In at least one embodiment, the system boundary 618 may be part of the detector 608 and the encoder and transmitter 616 even though shown together. In at least one embodiment, the server 604 and computing devices 610-614 may be in different geographical locations, including downhole and surface areas.

[0093] A signal detector 608 of a downhole tool 620 is provided to test the downhole elemental composition in a downhole environment 622. In at least one embodiment, the signal may be a natural GR signal or a return signal associated with neutron induced gamma spectroscopy. Thus, the downhole tool 620 may emit medium energy neutrons into the downhole environment 622. In at least one embodiment, a system for analyzing elements of a downhole environment includes a LWD system for analysis, wherein such a system may be adapted to transmit information received in the system from the downhole environment to a surface environment by wire or wireless. In at least one embodiment, modeling in the encoder and transmitter 616 may be performed using different predetermined fitting curves, allowing for further changes in the predetermined fitting curves than just slope and intercept changes.

[0094] The encoder and transmitter 616 can communicate with a photomultiplier tube 618, which communicates with the crystal scintillator 608. In at least one embodiment, each predetermined fit curve may require specific input from the server 604 for fitting the input received from the gamma ray signal. In at least one embodiment, a trained ML / AI algorithm (machine learning (ML) or artificial intelligence (AI)) can be used with each predetermined fit curve forming an activation function to classify logarithmic data for different energy windows of the signal. In at least one embodiment, the minimum error can reinforce the use of the same predetermined fit curve for future data of different energy windows of the signal.

[0095] In at least one embodiment, one or more components 604A-N may be adapted to function as a signal supply or detector device within server 604. In at least one embodiment, one or more components 604A-N may include one or more processors and one or more memory devices adapted to function as a detector or receiver device, while other processors and memory devices in server 604 may perform other functions.

[0096] In at least one embodiment, the server 604 may also provide software-based services or applications in a virtual or physical environment (such as to support the simulations referenced herein). In at least one embodiment, when the server 604 is a virtual environment, then the components 604A-N are software components that can be implemented on the cloud. In at least one embodiment, this feature allows real-time remote operation of a system for analyzing KUTh elemental composition using a downhole tool-dependent LWD system, as at least referenced herein. Figure 1 5. In at least one embodiment, this feature also allows remote access to information received and transmitted between any of the aforementioned devices. In at least one embodiment, one or more components 604A-N of server 604 may be implemented in hardware or firmware, rather than software implementations as described throughout this document. In at least one embodiment, combinations of these may also be used.

[0097] In at least one embodiment, one computing device 610-614 can be an intelligent monitor or display having at least a microcontroller and a memory having instructions that enable display of information monitored by the detector. In at least one embodiment, one computing device 610 can be a transmitter device to send directly to a receiver device or to a receiver device that can be part of an encoder and transmitter 616 via a network 606 and to a server 604 and other computing devices 612, 614. In at least one embodiment, the encoder and transmitter 616 can be separate components of a separate encoder and a separate transmitter even if shown together. The encoder can include a processor that performs selection of a fitting curve from a predetermined fitting curve and difference calculation (error). The transmitter can control the transmission of the encoded data to a surface location by using one of the telemetry methods mentioned (e.g., mud pulse telemetry).

[0098] In at least one embodiment, the other computing devices 612, 614 may include portable handheld devices, which are not limited to smart phones, cellular phones, tablet computers, personal digital assistants (PDAs), and wearable devices (head-mounted displays, watches, etc.). In at least one embodiment, the other computing devices 612, 614 may operate one or more operating systems, including Microsoft Windows (Any generation) and / or various mobile operating systems, such as Windows Palm and / or their variations.

[0099] In at least one embodiment, the other computing devices 612, 614 may support applications designed as Internet-related applications, email, short messaging or multimedia messaging service (SMS or MMS) applications, and may use other communication protocols. In at least one embodiment, the other computing devices 612, 614 may also include a computer running a Microsoft Apple and / or In at least one embodiment, the other computing devices 612, 614 may be general-purpose personal computers and / or laptop computers running operating systems such as . or UNIX-like operating systems or other GNU / Linux operating systems (such as Google Chrome ) workstation. In at least one embodiment, a gaming system (Microsoft )'s thin client device may be used as other computing devices 612, 614.

[0100] In at least one embodiment, network 606 can be any type of network capable of supporting data communications using a variety of protocols, including TCP / IP (Transmission Control Protocol / Internet Protocol), SNA (Systems Network Architecture), IPX (Internetwork Packet Exchange), In at least one embodiment, network 606 can be based on Ethernet, token ring, wide area network, Internet, virtual network, virtual private network (VPN), local area network (LAN), intranet, extranet, public switched telephone network (PSTN), infrared network, wireless network (such as according to the 802.11 protocol suite from the Institute of Electrical and Electronics Engineers (IEEE), and / or any other wireless protocol or the like) and / or any combination of these and / or other networks.

[0101] In at least one embodiment, the server 604 runs a suitable operating system, including any of the operating systems described throughout this document. In at least one embodiment, the server 604 may also run some server applications, including HTTP (Hypertext Transfer Protocol) servers, FTP (File Transfer Protocol) servers, CGI (Common Gateway Interface) servers, Server, database server and / or their variants. In at least one embodiment, database 602 is supported by database server features of server 604 with front-end capabilities. In at least one embodiment, such database server features include (International Business Machines) and / or their variants.

[0102] In at least one embodiment, the server 604 can provide a feed and / or real-time updates to the media feed. In at least one embodiment, the server 604 is part of a plurality of server boxes scattered across the region, but is used for the presently described process for analyzing porous formations. In at least one embodiment, the server 604 includes an application for measuring network performance through network monitoring and traffic management. In at least one embodiment, a database 602 is provided that enables storage of information from the well site, including user interactions, usage pattern information, adaptation rule information, and other information.

[0103] Although the technology herein is subject to modification and alternative construction, these changes are within the spirit of the present disclosure. Thus, certain illustrative embodiments are shown in the drawings and have been described in detail above, but these do not limit the disclosure to the particular form disclosed; on the contrary, all modifications, alternative constructions and equivalents falling within the spirit and scope of the present disclosure as defined in the appended claims are covered.

[0104] In the context of describing the disclosed embodiments (especially in the context of the appended claims), terms such as "a," "an," "the," and similar referents are understood to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context, and are not intended to be definitions of the terms. Include, have, include, and contain are understood to be open-ended terms (meaning phrases such as, but not limited to, including), unless otherwise noted. Connected, when unmodified and referring to a physical connection, may be understood as partially or fully contained within, attached to, or joined together, even if something intervenes.

[0105] Unless otherwise indicated herein, the enumeration of numerical ranges herein is intended only to be used as a shorthand method for individually referring to each individual numerical value falling within the range, and each individual numerical value is incorporated into the specification as if it were individually enumerated herein. In at least one embodiment, unless otherwise indicated or contradictory to the context, the use of terms such as sets (for item sets) or subsets is understood to be a non-empty set including one or more members. In addition, unless otherwise indicated or contradictory to the context, the term subset of a corresponding set does not necessarily represent a true subset of the corresponding set, but a subset and a corresponding set may be equal.

[0106] Connective language, such as the form phrase, at least one of A, B, and C or at least one of A, B, and C, unless otherwise specifically stated or otherwise clearly contradicted by context, should be understood as the context in which items, terms, etc. are usually presented can be A or B or C, or any non-empty subset of the set of A and B and C. In at least one embodiment of a set with three members, a connective phrase (such as at least one of A, B, and C and at least one of A, B, and C) refers to any of the following sets: {A}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B,, C}. Thus, such connective language is generally not intended to imply that certain embodiments require at least one of A, at least one of B, and at least one of C to be present. In addition, unless otherwise stated or contradicted by context, terms such as plural indicate a plural state (such as, a plurality of items means a plurality of items). In at least one embodiment, the number of the plurality of items is at least two, but may be more when so indicated explicitly or by context.In addition, unless otherwise specified or otherwise clear from context, phrases such as based on mean at least partially based on rather than solely based on.

[0107] The operations of the method in Figure 5 and the substeps described herein may be performed in any suitable order unless otherwise specified herein or otherwise clearly contradicted by the context. In at least one embodiment, the method includes a process such as those described herein (or variations and / or combinations thereof), which may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed jointly or exclusively on one or more processors by hardware or a combination thereof.

[0108] In at least one embodiment, such code may be stored on a computer-readable storage medium. In at least one embodiment, such code may be a computer program having instructions executable by one or more processors. In at least one embodiment, the computer-readable storage medium is a non-transitory computer-readable storage medium that excludes transient signals (such as propagating transient electrical or electromagnetic transmissions) but includes non-transitory data storage circuitry (such as buffers, caches, and queues) within a transceiver of transient signals. In at least one embodiment, code (such as executable code or source code) is stored on a set of one or more non-transitory computer-readable storage media (or other memory storing executable instructions) on which executable instructions are stored, which, when executed (such as as a result of being executed) by one or more processors of a computer system, causes the computer system to perform the operations described herein.

[0109] In at least one embodiment, a set of non-transitory computer-readable storage media includes a plurality of non-transitory computer-readable storage media, and one or more of the individual non-transitory storage media in the plurality of non-transitory computer-readable storage media lack all code, while the plurality of non-transitory computer-readable storage media collectively store all code. In at least one embodiment, the executable instructions are executed so that different instructions are executed by different processors - in at least one embodiment, the non-transitory computer-readable storage instructions store instructions, and the main central processing unit (CPU) executes some of the instructions, while other processing units execute other instructions. In at least one embodiment, different components of the computer system have separate processors, and different processors execute different subsets of instructions.

[0110] In at least one embodiment, the computer system is configured to implement one or more services that individually or collectively perform the operations of the processes described herein, and such computer system is configured with applicable hardware and / or software that enables the operations to be performed. In at least one embodiment, the computer system implementing at least one embodiment of the present disclosure is a single device, or a distributed computer system with multiple devices that operate differently, such that the distributed computer system performs the operations described herein and such that a single device does not perform all operations.

[0111] In at least one embodiment, even though the above discussion provides at least one embodiment with a specific implementation of the described techniques, other architectures may be used to implement the described functionality and are intended to be within the scope of the present disclosure. Additionally, although specific responsibilities may be assigned to components and processes, they are defined above for discussion purposes, and the various functions and responsibilities may be assigned and divided in different ways depending on the circumstances.

[0112] In at least one embodiment, although the subject matter has been described in language specific to structures and / or methods or processes, it should be understood that the subject matter claimed in the appended claims is not limited to the specific structures or methods described. Rather, the specific structures or methods are disclosed as example forms of how the claims may be implemented.

[0113] Based on all the above, it will be readily understood by those skilled in the art that the tools of the present disclosure provide numerous technical and commercial advantages and can be used in a variety of applications. Various embodiments can be combined or modified based in part on the present disclosure, which is readily understood to support such combinations and modifications to achieve the above benefits.

[0114] Thus, a method for data processing in downhole operations may include providing a downhole tool to receive a signal from a downhole environment, and determining coded data for the signal. The coded data may be based in part on coefficients associated with a transform function of data of different energy windows applied to the signal. For example, the coded data is from coded coefficients and a difference indicator to provide coded data representing a curve of the signal. The coefficients and the difference indicator may include at least one error between the data of the different energy windows of the signal and at least one predetermined fit curve. The method includes sending the coded data from the downhole environment to a surface environment, and determining at least one parameter or level of one or more elements in the downhole environment based in part on decoding the coded data.

[0115] Such methods may also include determining the levels of at least potassium, uranium, and thorium, which may be one or more elements or associated with at least one parameter in the downhole environment. In addition, such methods utilize logarithmic data of different energy windows, wherein the transformation function is a logarithmic transformation function. The method may also include performing curve fitting between the data of different energy windows of the signal and a plurality of different predetermined fitting curves. Such predetermined fitting curves may be logarithmic regression curves with different slopes and different intercepts, and may fit input curves of different energy windows. The method may include selecting at least one predetermined fitting curve from the predetermined fitting curves based at least in part on the statistical significance of at least one error within a predetermined threshold.

[0116] The method may include, as part of decoding at the surface environment, using coefficients from the encoded data to generate representative data (such as logarithmic data). An inverse function (such as an inverse logarithmic function) may then be performed on the representative data to generate count data for different energy windows. The method includes analyzing the count data to arrive at a level (occurrence) of at least one element such as potassium, uranium, or thorium in the downhole environment.

[0117] In at least one embodiment, the method includes using a slope as a coefficient that contributes a 3-bit value to the encoded data, an intercept that contributes a 3-bit value to the encoded data, and at least one error that contributes a 4-bit value to the encoded data. Again, a 3-bit value may be an example; and the transform function coefficients may include a third-order polynomial with 4 coefficients, and provide enough bits to support this, but such that the total bits remain compressed relative to other methods.

[0118] In at least one embodiment, the 4-bit value includes n bits (+1) representing the sign of at least one error. The method herein includes using an allocated number of different energy windows of the signal to form a portion of the encoded data, and performing the transmission of the encoded data at a predetermined communication speed. In at least one embodiment, the method herein includes providing a total of 42 bits of encoded data for each depth position of a downhole tool. For example, in the case of 9 windows with 4 bits per value in addition to the 2x3 intercept and slope, there may be many other sizes that still represent compressed data relative to using all provided bits for communication.

[0119] In at least one embodiment, a method for data processing in downhole operations is disclosed. In at least one embodiment, the method includes providing a downhole tool to receive a signal from a downhole environment. Another step in the method includes determining coded data of the signal. The coded data may be based in part on coefficients associated with a transformation function applied to data from different regions of the signal. In at least one embodiment, the coefficients include at least one error between data from different regions of the signal and at least one predetermined fit curve. In at least one embodiment, the method includes sending the coded data from the downhole environment to a surface environment. In addition, the method includes determining at least one parameter or level of different elements in the downhole environment based in part on decoding the coded data.

[0120] In at least one embodiment, a system for data processing in downhole operations includes: a downhole tool for receiving a signal from a downhole environment; and at least one processor and a memory, the memory including instructions that cause the system to perform functions when executed by the at least one processor. The functions include determining coded data of the signal. The coded data is based in part on coefficients associated with a transform function. The coefficients may include a slope, an intercept, and at least one error. The at least one error may be between data of different energy windows of the signal and at least one predetermined fit curve. The functions include sending the coded data from the downhole environment to the surface environment. Additional functions include determining at least one parameter or level of at least one element in the downhole environment based in part on decoding the coded data.

Claims

1. A method (500; 550), characterized in that: providing (502; 552) a downhole tool to receive a signal from a downhole environment within a wellbore, the signal defining a signal curve; determining (554) coefficients of a fitting curve that fits the signal curve; determining (556) a difference indicator representing a difference between the signal curve and the fitted curve; encoding (504; 558) the coefficients and the difference indicator to provide encoded data representing the signal curve; transmitting (508; 562) the encoded data from the downhole environment to a surface environment outside the wellbore; decoding the encoded data at the terrestrial environment (564) to provide decoded data; as well as At least one parameter of the downhole environment is determined (510; 566) based in part on the decoded data.

2. The method of claim 1, wherein the signal curve comprises a plurality of count rates in a plurality of energy windows, and the at least one parameter of the downhole environment comprises the presence of at least one radioactive element in the downhole environment.

3. The method according to claim 1, further characterized in that: A pulsed neutron source is provided in the downhole tool, the pulsed neutron source being associated with neutron induced gamma radiation in the downhole environment, wherein the signal received from the downhole environment is related to the neutron induced gamma radiation.

4. The method of claim 2, wherein in the downhole environment, the at least one radioactive element comprises one of potassium, uranium, or thorium.

5. The method according to claim 2, further characterized in that: generating a decoded signal curve using the decoded data as part of performing the decoding at the terrestrial environment; and Inverse modeling is performed based on the decoded signal curve to determine the occurrence of the at least one radioactive element in the downhole environment.

6. The method according to claim 1, further characterized in that: subjecting the signal curve to a transformation function to provide a transformed signal curve; and The fitting curve is determined based on the transformed signal curve. 7 . The method of claim 6 , wherein the transformation function is one of a log2 function, an arctangent transformation function, a square root transformation function, or an exponential power transformation function. The method of claim 1 , wherein the coefficients include a slope and an intercept.

9. The method of claim 1, wherein the signal curve comprises count rates in at least five energy windows.

10. The method of claim 1, wherein the encoded data comprises a predetermined number of bits.

11. The method of claim 1, wherein the encoded data comprises a variable number of bits, wherein the variable number of bits depends on a predetermined error, and wherein the predetermined error is related to a difference between the signal curve and a decoded signal curve generated from the decoded data.

12. The method of claim 1, further comprising performing a wellbore operation based on the determined at least one parameter of the downhole environment, wherein the wellbore operation comprises one of log generation or change of an operation parameter.

13. The method of claim 1, wherein transmitting the encoded data comprises transmitting less than 10 bits per second from the downhole environment to the surface environment.

14. The method of claim 1, wherein transmitting the encoded data comprises one of mud pulse telemetry, acoustic telemetry, or electromagnetic telemetry.

15. The method of claim 1, wherein the fitted curve is a predetermined fitted curve, and wherein the coefficients are stored in a memory in the downhole tool.

16. The method of claim 1, wherein receiving the signal from the downhole environment is further characterized by: A first signal is received at a first borehole depth defining a first signal curve and a second signal is received at a second borehole depth defining a second signal curve, first coefficients of the fitting curve are determined to fit the first signal curve and second coefficients of the fitting curve are determined to fit the second signal curve.

17. A system (100; 600) for data processing in downhole operations, the system being characterized by: a downhole tool (116; 620) for receiving a signal from a downhole environment within a wellbore, the signal defining a signal curve; a memory (604A) storing instructions; and a processor (604B) configured to execute the instructions from the memory to cause the system to: determining (554) coefficients of a fitting curve that fits the signal curve; determining (556) a difference indicator representing a difference between the signal curve and the fitted curve; encoding (504; 558) the coefficients and the difference indicator to provide encoded data representing the signal curve; transmitting (508; 562) the encoded data from the downhole environment to a surface environment outside the wellbore; decoding the encoded data at the terrestrial environment (564) to provide decoded data; as well as At least one parameter of the downhole environment is determined (510; 566) based in part on the decoded data.

18. The system of claim 17, wherein the instructions, when executed by the processor, further cause the system to: subjecting the signal curve to a transformation function to provide a transformed signal curve; and The fitting curve is determined based on the transformed signal curve.

19. The system of claim 17, wherein the instructions, when executed by the processor, further cause the system to: generating a decoded signal curve using the decoded data as part of performing the decoding at the terrestrial environment; and Inverse modeling is performed based on the decoded signal curve to determine the occurrence of at least one radioactive element in the downhole environment.

20. The system of claim 17, wherein the signal profile comprises a plurality of count rates in a plurality of energy windows and the at least one parameter in the downhole environment comprises the presence of at least one radioactive element in the downhole environment.

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