Array induction high signal-to-noise ratio subarray curve estimation method and system

Abstract

The invention relates to an array induction high signal-to-noise ratio subarray curve estimation method and system. The estimation method comprises the following steps that the stratum conductivity when gas is completely contained is calculated to serve as a theoretical conductivity lower limit; and constructing a constraint condition based on the conductivity curve of each sub-array, and correcting the conductivity curve of each sub-array based on the constraint condition and the theoretical conductivity lower limit to obtain a corrected sub-array curve. According to the method, the theoretical conductivity lower limit value is estimated by comprehensively reflecting data such as an experiment of rock physical characteristics of a complex carbonate rock stratum, a porosity logging curve and the like, so that high-signal-to-noise-ratio curve optimization and abnormal value correction are carried out on an array induction logging original sub-array curve which is influenced by a complex shaft environment, high temperature and high pressure and is relatively low in overall signal-to-noise ratio; it is ensured that the overall quality of the corrected conductivity curve meets the follow-up processing requirement, and an accurate resistivity curve is provided for gas-bearing recognition and reserve calculation of the complex stratum.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the technical field of oil exploration, and particularly relates to an array induction high signal-to-noise ratio subarray curve estimation method and system. BACKGROUND

[0002] With the continuous deepening of domestic oil and gas exploration and development, advancing into the deep part of the earth has been the main direction in the present and a long time to come. The overall carbonate rock formation is dense, with high background resistivity and low conductivity. In deep carbonate rock drilling, oil-based mud is often used to protect the stability of the well wall, so that array induction logging can only be used when the open hole is logged. The instrument adopts a subarray combination design with multiple source distances to measure the conductivity signals in different detection ranges. Due to the extremely low background conductivity of deep carbonate rock formations, combined with the temperature drift of the instrument circuit caused by high temperature, and the influence of multiple factors such as high-resistance oil-based mud and local expansion on the short-source-distance subarray, the original conductivity signals collected by multiple subarrays of the array induction instrument, especially the subarrays with shorter source distances, often have negative value abnormalities, and the processing results do not reflect the actual petrophysical characteristics of the formation, which cannot be used for gas layer identification and evaluation.

[0003] For signal processing of array induction logging, a large number of domestic imported foreign commercial software platforms (for example, the processing software Express matched with the HDIL instrument of the American Baker Hughes Company) are used. The platform is sold with the instrument, and the user directly obtains the output array resistivity by inputting the HDIL original data and the matched curve in the specified format, and the processing flow in the middle is a "black box" that cannot be customized or modified.

[0004] For the above-mentioned negative abnormal signals, the software uses a conductivity of 0.5 mS / m as the lower limit for forced assignment in the subsequent borehole correction link, and does not consider the signal-to-noise ratio difference of different subarrays, and all curves are input, and the output resistivity curves at different detection depths are flat and overlapped, which neither reflect the longitudinal petrophysical characteristic changes of the reservoir nor can be used for gas layer identification and reserve calculation.

[0005] The research of a large number of domestic scholars mainly focuses on how to invert the invasion characteristics and original formation resistivity Rt of the stratum based on the multiple detection depth and multiple resolution curves provided by the array induction logging. However, the premise of all these researches should be that the resistivity profile output by the array induction logging is accurate and reasonable. Under the above-mentioned adverse well conditions and complex formation background, the original signals of the array induction logging have a large number of abnormalities, and the output resistivity profile basically does not contain useful signals, so all these inversion researches have limitations. SUMMARY

[0006] The purpose of the present disclosure is to provide an array induction high signal-to-noise ratio subarray curve estimation method and system to solve the above problems.

[0007] The present disclosure achieves the above-mentioned purpose by the following technical solutions:

[0008] An array induction high signal-to-noise ratio subarray curve estimation method comprises the following steps:

[0009] Obtaining reservoir rock-electricity parameters of a target block, array induction logging subarray conductivity curves of a target well to be processed, and a formation porosity curve;

[0010] Setting that the formation is completely gas-bearing, and calculating the formation conductivity when completely gas-bearing as a theoretical conductivity lower limit based on the reservoir rock-electricity parameters and the formation porosity curve;

[0011] Constructing a constraint condition based on the subarray conductivity curves, correcting the subarray conductivity curves based on the constraint condition and the theoretical conductivity lower limit, and obtaining corrected subarray curves.

[0012] As a further optimization scheme of the present disclosure, obtaining the reservoir rock-electricity parameters of the target block comprises:

[0013] Performing high-temperature and high-pressure rock-electricity experiments on the target block to obtain reservoir rock-electricity parameters a, b, m, n, and resistivity R w and formation irreducible water saturation S wi .

[0014] As a further optimization scheme of the present disclosure, obtaining the formation irreducible water saturation S wi comprises:

[0015] Determining the irreducible water saturation of each full-diameter sample by using the partition plate displacement method, and taking the minimum value of the experimental results of all samples as S wi .

[0016] As a further optimization scheme of the present disclosure, the specific process of calculating the theoretical conductivity lower limit is as follows:

[0017] Setting that the formation is completely gas-bearing, i.e., the fluid in the pore is irreducible water and natural gas, according to the Archie saturation calculation formula, the water saturation is equal to the formation irreducible water saturation S wi , at this time, the resistivity of the formation reaches its theoretical upper limit, and the conductivity reaches its theoretical lower limit;

[0018] Calculating the theoretical conductivity lower limit σ tmin using the related parameters determined by experiments, and the calculation formula is:

[0019]

[0020] wherein σ w = 1 / R w , represents the conductivity of the formation water; R w represents the resistivity; the formation porosity curve Φ; S wi represents the formation irreducible water saturation; a, b, m, n are the reservoir rock electrical parameters.

[0021] As a further optimization scheme of the present disclosure, the specific steps of constructing a constraint condition based on the conductivity curves of the sub-arrays, correcting the conductivity curves of the sub-arrays based on the constraint condition and the lower limit of the theoretical conductivity, and obtaining the corrected sub-array curves are as follows:

[0022] The conductivity curves σ isec of the sub-arrays are compared with the lower limit σ tmin of the theoretical conductivity, and if σ isec < σ tmin , then σ isec = σ tmin , that is, it is ensured that σ isec ≥ σ tmin for each sampling point in the measured well section, the corrected curve is recorded as σ isec_cor , and the number of data points M i that have changed is counted at the same time.

[0023] The M1 and M2 corresponding to the conductivity curves σ 1sec and σ 2sec of the two sub-arrays with the shortest source distance are analyzed, and if M1 accounts for more than a first preset value of the total number of sampling points in the entire treated well section, then σ 1sec is discarded; if M2 accounts for more than a second preset value of the total number of sampling points, then σ 1sec and σ 2sec are discarded at the same time.

[0024] The sub-array curve σ isec_cor remaining after correction is the corrected sub-array curve.

[0025] As a further optimization scheme of the present disclosure, the first preset value is 50%, and the second preset value is 30%.

[0026] As a further optimization scheme of the present disclosure, the correction judgment is mainly for the sub-arrays with the shortest source distance, and if the conductivity curves of multiple sub-arrays are abnormal, then further judgment is made on other sub-arrays.

[0027] An array induction high signal-to-noise ratio sub-array curve estimation system, comprising:

[0028] The data acquisition module is configured to acquire reservoir litho-electric parameters of the target block, array induction logging sub-array conductivity curves and formation porosity curves of the target well to be processed.

[0029] The calculation module is configured to set the formation as completely gas-bearing, and calculate formation conductivity when the formation is completely gas-bearing as a theoretical conductivity lower limit based on the reservoir litho-electric parameters and the formation porosity curve.

[0030] The correction module is configured to construct a constraint condition based on the sub-array conductivity curves, and correct the sub-array conductivity curves based on the constraint condition and the theoretical conductivity lower limit to obtain corrected sub-array curves.

[0031] An electronic device, characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus;

[0032] The memory is configured to store a computer program.

[0033] The processor is configured to implement the array induction high signal-to-noise ratio sub-array curve estimation method when executing the program stored in the memory.

[0034] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement an array induction high signal-to-noise ratio sub-array curve estimation method.

[0035] The present disclosure has the following beneficial effects:

[0036] The present disclosure comprehensively reflects the experimental data, porosity logging curve and other data of the petrophysical characteristics of the complex carbonate rock formation to estimate the theoretical conductivity lower limit value thereof, and based on the same, the original sub-array curves of the array induction logging affected by the complex wellbore environment and high temperature and high pressure and having a low overall signal-to-noise ratio are subjected to high signal-to-noise ratio curve optimization and abnormal value correction, so as to ensure that the overall quality of the corrected conductivity curves meets the subsequent processing requirements, and then the subsequent processing is carried out with the aid of commercial software, so as to obtain a reasonable output resistivity profile, thereby providing accurate resistivity curves for gas identification and reserve calculation of such complex formations. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a method flowchart of the present disclosure;

[0038] Figure 2 is a comprehensive diagram of array induction original conductivity and processing results of research area wells in an embodiment of the present disclosure;

[0039] Figure 3 is a comparison diagram of array induction sub-array curve constraint correction before and after correction in an embodiment of the present disclosure;

[0040] Figure 4 is a well water layer section treatment result comparison chart in the research area in the embodiment of the disclosure;

[0041] Figure 5 is a well water layer section treatment result comparison chart in the research area in the embodiment of the disclosure;

[0042] Figure 6 is a system structure block diagram in the embodiment of the disclosure;

[0043] Figure 7 is an equipment structure block diagram in the embodiment of the disclosure. DETAILED DESCRIPTION

[0044] It is necessary to point out here that the following detailed description is only used to further illustrate the application, and cannot be understood as limiting the scope of protection of the application. Those skilled in the art can make some non-essential improvements and adjustments to the application according to the above application content.

[0045] As shown in Figure 1 , an array induction high signal-to-noise ratio subarray curve estimation method comprises the following steps:

[0046] Obtain the reservoir rock-electricity parameters of the target block, the array induction logging subarray conductivity curves of the target well to be processed, and the formation porosity curve;

[0047] Set the formation to be completely gas-filled, and calculate the formation conductivity when completely gas-filled as the lower limit of the theoretical conductivity based on the reservoir rock-electricity parameters and the formation porosity curve;

[0048] Based on the constraint condition and the lower limit of the theoretical conductivity, the subarray conductivity curves are corrected to obtain the corrected subarray curves.

[0049] The reservoir rock-electricity parameters of the target block include:

[0050] Perform high-temperature and high-pressure rock-electricity experiments on the target block to obtain the reservoir rock-electricity parameters a, b, m, n, resistivity R w , and formation irreducible water saturation S wi .

[0051] The disclosure specifically includes:

[0052] Collect the rock-electricity experiment and formation water test results a, b, m, n, S wi , R w of the target block; collect the array induction logging subarray conductivity curves σ isec (i=1, N) and the formation porosity curve Φ of the target well to be processed;

[0053] According to Archie saturation calculation formula, assuming that the formation is completely gas, i.e. the fluid in the pore is irreducible water + natural gas, the water saturation is equal to S wi At this time, the resistivity of the formation reaches its theoretical upper limit, and the conductivity reaches its theoretical lower limit. The related parameters determined by the experiment are used to calculate the theoretical conductivity lower limit σ tmin , the calculation formula is In the formula, σ w =1 / R w , is the conductivity of formation water;

[0054] For each subarray conductivity curve σ isec of the array induction logging (i=1, N, N is the number of subarrays), compare σ isec and σ tmin , if σ isec <σ tmin , then σ isec =σ tmin , that is, ensure that σ isec ≥σ tmin at each sampling point in the measured well section, and the corrected curve is denoted as σ isec_cor , and the number of data points M i that have changed is also counted at the same time;

[0055] Analyze M1 and M2 corresponding to the shortest source distance of two subarray conductivity curves σ 1sec and σ 2sec , if M1 accounts for more than 50% of the total number of sampling points in the entire processed well section, it is considered that the signal-to-noise ratio of the σ 1sec curve is too low and is not suitable for subsequent processing, and is discarded; if M2 accounts for more than 30% of the total number of sampling points, it is considered that the signal-to-noise ratio of the σ 2sec curve is too low and is not suitable for subsequent processing, and the σ 1sec and σ 2sec curves are discarded at the same time;

[0056] For the subarray curves σ isec_cor that have been corrected and retained through the above constraints, subsequent processing such as borehole correction and resolution matching is carried out, and the array resistivity results are output for gas layer evaluation;

[0057] Rock-electricity experiment is a displacement rock-electricity experiment under actual reservoir temperature and pressure for full-diameter core samples containing holes and fractures. For a research block, the lithology types and reservoir types of the experimental samples should be representative and cover all actual reservoir types.

[0058] R w refers to the resistivity converted to the formation temperature and pressure conditions according to the total salinity and density determined by the analysis of the actual water sample;

[0059] Mud conductivity curve σ m Should be the result of simultaneous acquisition with array induction logging to ensure the matching of the two;

[0060] Irreducible water saturation is determined for each full diameter sample using the spacer displacement method, and the minimum value of all sample experimental results is taken as S wi ;

[0061] Archie formula calculation process, the unified S wi of the entire treated well section. Since this variable is the lowest value of the experimental analysis of the irreducible water saturation of all reservoir type samples, the formula calculates the lower limit of the theoretical conductivity of all reservoir types;

[0062] If M1 accounts for more than 50% of the total number of sampling points, it means that the signal-to-noise ratio of the σ1 curve is too low, and the wellbore effect is too large, so it is not suitable for further processing, and the σ1 curve is discarded;

[0063] If M2 accounts for more than 30% of the total number of sampling points, it means that the signal-to-noise ratio of the σ2 curve is too low, and the wellbore effect is too large, so it is not suitable for further processing, and the σ2 curve is discarded;

[0064] If the σ2 curve is discarded, no matter how much M1 accounts for, the σ1 curve also needs to be discarded;

[0065] The array induction logging instrument is designed with multiple source distance sub-arrays, among which the long source distance sub-array is relatively small. Therefore, the curve discarding judgment described in step 4 is mainly for the shortest source distance sub-arrays 1 and 2. If the original data quality is particularly poor, multiple original sub-array curves are abnormal, then the method is used to further judge sub-arrays 3 and 4.

[0066] In this embodiment, it specifically comprises:

[0067] For the target layer of the study area, the reservoir rock and electricity parameters a=1.05, b=1.12, m=1.95, n=2.07, R w =0.054Ω.m, and the formation irreducible water saturation S wi =40% are determined by high temperature and high pressure rock and electricity experiments. For the well to be processed, the porosity curve is calculated using the regional model or theoretical formula, denoted as POR; The array induction logging original data of the well is collected, and the conductivity logging curves of each sub-array after processing are denoted as σ isec (i=1,7), such as Figure 2The following figure shows the raw conductivity curves at eight frequencies for the seven subarrays of the HDIL instrument in an actual oil-based mud well in carbonate formations, along with the theoretical conductivity lower limit curve estimated based on experimental analysis data and porosity curves. Subarrays 1 to 7 in the figure represent seven subarray channels, each with the SGMAij curve, where i represents the subarray number and j represents the subarray's operating frequency number. It can be seen that the well was drilled at a depth of over 7,000 meters using oil-based mud. Due to the harsh environment, the short-source-distance subarrays 1 and 2 exhibit negative raw conductivity curves for all eight frequencies, which do not reflect the true characteristics of the formation. Subarray 3 performs relatively well. With the exception of the negative SGMA31 curve for frequency 1, the curves for the other frequencies oscillate around the zero line. The conductivity curves for each frequency of subarrays 4 to 7 gradually return to normal. Channel 10 in the figure shows the conductivity curve σ after seven subarrays. isec , indicating that the short source distance subarray σ 1sec and σ 2sec The curves are significantly abnormal, with negative values ​​appearing at multiple depths and unable to be displayed on the logarithmic scale. Track 11 is an array resistivity profile generated using commercial software based on the aforementioned data. The curves at different depths completely overlap, and in most well sections, the curves are flat, failing to reflect the true petrophysical characteristics of the formation.

[0068] Using Archie's formula, calculate the formation when it is completely gas-bearing (let the formation water saturation S w =S wi =40%) of the theoretical resistivity curve R t , whose reciprocal is the theoretical lower limit of the conductivity of the formation, denoted as σ tmin , as attached Figure 3 The fourth blue curve.

[0069] For each curve σ isec , analyze its value and σ point by point tmin The size relationship of σ isec <σ tmin , then the mandatory assignment is σ isec =σ tmin , and record the number of changed sampling points M i , as attached Figure 3 As shown in Track 5, Figure 3 The curve after 7 sub-arrays of array induction logging of a certain well is compared with the result after the theoretical conductivity lower limit constraint. In the figure, the third track is the original curve after 7 sub-arrays of array induction logging. The shortest source distance σ 1secThe curve is mostly negative throughout the entire well section, with anomalies occurring in almost all subarrays in the 7770-7775m section (the logarithmic scale cannot be displayed, and only a few points respond normally). Track 4 shows the lower limit of formation conductivity estimated using the Archie saturation formula. Track 5 shows the result of applying lower limit constraints and signal-to-noise ratio screening to the seven subarrays. It can be seen that most of the curve values ​​for subarray 1 are constrained, resulting in a very low signal-to-noise ratio and should be discarded. Track 6 shows the borehole correction result for the original unconstrained data, and Track 7 shows the borehole correction result after applying the conductivity lower limit constraint, with σ being discarded. 1sec curve.

[0070] Determine the M of each subarray i Whether the proportion of the total number of sampling points exceeds a certain limit. For the shortest source distance subarray 1, which is most affected by the wellbore, if the proportion of M1 exceeds 50%, it is considered that its signal-to-noise ratio is too low and the curve σ is discarded in subsequent processing. 1sec Subarray 2 is less affected by the wellbore than subarray 1. If the proportion of M2 exceeds 30%, the signal-to-noise ratio is considered too low and the curve σ is discarded in subsequent processing. 2sec , while also discarding σ 1sec .

[0071] For complex well conditions such as irregular well wall and serious expansion, we also need to judge subarray 3 and set the upper limit of signal-to-noise ratio in a similar way. 3sec , then we also discard σ 2sec , σ 1sec .

[0072] Generally, the three sub-arrays with the longest source distance of the array sensing instrument have a large detection depth and are less affected by the wellbore. To ensure sufficient information for subsequent processing, these three curves are also subject to lower limit constraints but are not discarded.

[0073] After the above correction, the retained conductivity curve is processed by commercial software for subsequent borehole correction and resolution matching, and the resistivity curves at different detection depths are output, as shown in the attached figure. Figure 4 , Attachment Figure 5 The fourth step is to determine the gas content. Figure 3For the method of the present application, the treatment results of a certain well water layer section are compared. In the figure, the third track is the output result of the software focusing processing directly using the commercial software without constraint correction of the original data, and the resistivity curves at different detection depths of the entire well section completely overlap, especially there is no separation in the tested water layer section, and the result does not conform to the petrophysical characteristics of the formation; the fourth track is the result of the signal-to-noise ratio screening using the method of the present application, the subarray 1 and subarray 2 curves are removed, and then the software focusing processing is applied by using the commercial software, and the deep detection resistivity in the water layer section is lower than the shallow detection resistivity, that is, the resistivity increases with the invasion. This is because the oil-based mud invades the formation, which increases the resistivity IR2 of the invasion zone near the well wall, and the deep detection resistivity IR5 reflects the original resistivity of the true formation, and the water layer resistivity is low. Therefore, the result obtained by using the method of the present application is more in line with the petrophysical characteristics of the formation. Figure 4 For another well water layer section treatment result comparison. In the figure, the original data without constraint processing result (the third track) appears abnormal in the 5, 6 and 7 sublayers, and the shallow detection resistivity curves at multiple depth positions are opposite to the deep detection resistivity curves, which is because the short source distance subarray is greatly affected by the oil-based mud in the wellbore and has low signal-to-noise ratio, and the resistivity at different detection depths output after participating in the processing shows a "mirror feature", which is completely inconsistent with the petrophysical law of the reservoir. By using the method of the present application, the subarray 1 curve is removed, and the processing result (the fourth track) shows the resistivity increase with the invasion in the water layer section, which is completely in line with the petrophysical law.

[0074] As shown in Figure 6 The embodiment of the present disclosure provides an array induction high signal-to-noise ratio subarray curve estimation system, which comprises:

[0075] A data acquisition module 11 is configured to acquire reservoir rock and electricity parameters of a target block, array induction logging conductivity curves of a target well to be processed, and a formation porosity curve;

[0076] A calculation module 12 is configured to set that the formation is completely gas-filled, and calculate the formation conductivity when the formation is completely gas-filled as a theoretical conductivity lower limit based on the reservoir rock and electricity parameters and the formation porosity curve;

[0077] A correction module 13 is configured to construct a constraint condition based on the conductivity curves of the subarrays, correct the conductivity curves of the subarrays based on the constraint condition and the theoretical conductivity lower limit, and obtain the corrected subarray curves.

[0078] The implementation process of the functions and roles of each module in the above system is specifically described in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0079] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts are described in the method embodiments. The above-described system embodiments are only illustrative, wherein the modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical modules, i.e., can be located in one place or distributed to multiple network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present disclosure. Those skilled in the art can understand and implement without creative labor.

[0080] In the above embodiments, any number of the modules can be combined in one module, or any one of the modules can be split into multiple modules. Alternatively, at least part of the function of one or more of the modules can be combined with at least part of the function of other modules, and implemented in one module. At least one of all the modules can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on substrate, a system on package, an application specific integrated circuit (ASIC), or any other reasonable way of integrating or packaging a circuit, or can be implemented by hardware or firmware, or any one of software, hardware and firmware or a suitable combination of any of them. Alternatively, at least one of all the modules can be at least partially implemented as a computer program module which can perform corresponding functions when executed.

[0081] Referring to Figure 7 The electronic device provided by the embodiments of the present disclosure includes a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120 and the memory 1130 complete mutual communication through the communication bus 1140.

[0082] The memory 1130 is used to store a computer program.

[0083] The processor 1110 is used to execute the program stored on the memory 1130, and implement the array sensing high signal-to-noise ratio subarray curve estimation method as shown below.

[0084] The communication bus 1140 described above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 1140 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is shown in the figure, but it does not mean that there is only one bus or only one type of bus.

[0085] The communication interface 1120 is configured to communicate between the electronic device described above and other devices.

[0086] The memory 1130 can include a Random Access Memory (RAM) and can also include a non-volatile memory, such as at least one disk memory. Optionally, the memory 1130 can also be at least one storage device located away from the aforementioned processor 1110.

[0087] The processor 1110 described above can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0088] Embodiments of the present disclosure also provide a computer readable storage medium. The computer readable storage medium described above stores a computer program, and the computer program is executed by a processor to implement the array sensing high signal-to-noise ratio subarray curve estimation method described above.

[0089] The computer readable storage medium can be included in the device / apparatus described in the above embodiments; or can exist separately and not be assembled into the device / apparatus. The computer readable storage medium described above carries one or more programs, and when the one or more programs are executed, the array sensing high signal-to-noise ratio subarray curve estimation method according to the embodiments of the present disclosure is implemented.

[0090] According to embodiments of the present disclosure, the computer readable storage medium can be a non-transitory computer readable storage medium, for example, can include but is not limited to: a portable computer diskette, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM or flash memory), a portable compact disc read only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0091] The above-described embodiments are merely illustrative of several embodiments of the present disclosure, which are described in a relatively specific and detailed manner, but should not be construed as limiting the scope of the patent of the present disclosure. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present disclosure, and these all belong to the protection scope of the present disclosure.

Claims

1. A method for estimating curves of high signal-to-noise ratio subarrays of an array, characterized in that, The method comprises the following steps: obtaining reservoir litho-electric parameters of a target block, array induction logging sub-array conductivity curves and formation porosity curves of a target well to be processed; setting that the formation is completely gas-bearing, calculating formation conductivity when the formation is completely gas-bearing as a theoretical conductivity lower limit based on the reservoir litho-electric parameters and the formation porosity curves; constructing a constraint condition based on the array induction logging sub-array conductivity curves, correcting the array induction logging sub-array conductivity curves based on the constraint condition and the theoretical conductivity lower limit to obtain corrected sub-array curves.

2. The method of claim 1, wherein, The reservoir litho-electric parameters of the target block are obtained by: The target block is subjected to high temperature and high pressure rock electricity experiment to obtain reservoir rock electricity parameters a, b, m, n and resistivity R w and formation irreducible water saturation S wi .

3. The method for estimating a high signal-to-noise ratio subarray curve for array sensing according to claim 2, characterized in that: acquiring the formation bound water saturation S wi comprising: The irreducible water saturation of each full diameter sample was determined by the separate barrier displacement method, and the minimum value of all sample experimental results was taken as S wi .

4. The method of claim 2, wherein, The specific process of calculating the theoretical conductivity lower limit is as follows: The formation is set to be completely gas-bearing, i.e. the fluid in the pore is bound water and natural gas, and according to the Archie saturation calculation formula, the water saturation is equal to the formation bound water saturation S wi At this time, the resistivity of the formation reaches the upper limit of its theoretical value, and the conductivity reaches the lower limit of its theoretical value. The lower limit of the theoretical conductivity σ is calculated using the experimentally determined correlation parameters tmin The calculation formula is: where σ w = 1R w , represents the conductivity of the formation water; R w represents the resistivity; the formation porosity curve Φ; S wi represents the formation irreducible water saturation; a, b, m, n are the reservoir petroelectric parameters.

5. The method of claim 4, wherein, The specific steps of constructing a constraint condition based on the array induction logging sub-array conductivity curves, correcting the array induction logging sub-array conductivity curves based on the constraint condition and the theoretical conductivity lower limit to obtain corrected sub-array curves are as follows: The sub-array conductivity curves σ isec and the theoretical conductivity lower limit σ tmin are compared, if σ isec < σ tmin , then σ isec = σ tmin , that is, it is ensured that σ isec ≥ σ tmin at each sampling point in the measured well section, the corrected curve is recorded as σ isec_cor , and the number of data points M i that have changed is counted simultaneously; analyzing the two sub-array conductivity curves σ 1sec and σ 2sec corresponding to M1 and M2, if M1 accounts for more than a first preset value of the total number of sampling points in the entire treatment interval, then σ 1sec is discarded; if M2 accounts for more than a second preset value of the total number of sampling points, then σ 1sec and σ 2sec are discarded simultaneously; Subarray curve σ remaining after correction isec_cor Subarray curve after correction.

6. The method of claim 5, wherein, The first preset value is 50%, and the second preset value is 30%.

7. The method of claim 5, wherein, The correction judgment is mainly for the sub-array with the shortest source distance. If the array induction logging sub-array conductivity curves are abnormal, further judgment is made on other sub-arrays.

8. An array sensing high signal-to-noise ratio subarray curve estimation system, characterized by, The method comprises the following steps: The data acquisition module is configured to obtain reservoir litho-electric parameters of a target block, array induction logging sub-array conductivity curves and formation porosity curves of a target well to be processed; The calculation module is configured to set that the formation is completely gas-bearing, calculate formation conductivity when the formation is completely gas-bearing as a theoretical conductivity lower limit based on the reservoir litho-electric parameters and the formation porosity curves; The correction module is configured to construct a constraint condition based on the array induction logging sub-array conductivity curves, correct the array induction logging sub-array conductivity curves based on the constraint condition and the theoretical conductivity lower limit to obtain corrected sub-array curves.

9. An electronic device, comprising: The device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus; The memory is configured to store a computer program; The processor is configured to execute the program stored in the memory to implement the array induction high-signal-to-noise ratio sub-array curve estimation method in any one of claims 1-7.

10. A computer readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the array induction high-signal-to-noise ratio sub-array curve estimation method in any one of claims 1-7.

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