Coal body structure quantitative division method based on logging response mechanism and application

Abstract

The present application belongs to the technical field of well logging, and relates to a coal structure quantitative division method based on well logging response mechanism and application. The coal structure of coal rock samples is preliminarily identified and divided. The well logging curve measurement data of different coal structures is obtained, and the well logging curve measurement data is normalized. Combined with the type of well logging curve measurement data, a fragmentation collapse factor and a conductive network factor are constructed. According to the fragmentation collapse factor and the conductive network factor, the normalized well logging curve measurement data is calculated, and according to the calculation result, a division standard of coal structure is established. The present application can be applied to the initial exploration and evaluation of deep buried coal rock gas reservoirs, comprehensively considers multiple conventional well logging sensitive curves, performs sensitive information fusion, constructs a fragmentation collapse factor and a conductive network factor sensitive curve, realizes continuous quantitative evaluation of coal structure, and improves the division precision of coal structure.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of well logging, and relates to a coal body structure quantitative division method based on well logging response mechanism and application. BACKGROUND

[0002] Coal body structure is a macroscopic description of the structural characteristics of coal rock reservoirs under the action of tectonic stress on the stress-strain of coal rock itself. According to the national standard GB / T 3005-2013, coal body structure can be divided into primary structure, fractured structure, granular structure and mylonitic structure. Due to the excessive strong tectonic movement, the coal body structure is easily damaged, which leads to the poor connectivity of cleats or even closure, increases the output of coal powder, and reduces the permeability of coal rock reservoirs, which is not conducive to reservoir reconstruction. Therefore, the accurate division of coal body structure has a crucial influence on the selection of favorable areas, reservoir evaluation and development and utilization of deep coal rock gas reservoirs.

[0003] The Jurassic thick coal rock reservoirs are developed in a certain basin, which is different from the traditional coalbed methane. More than 80% of the coal rock is buried at a depth of 2000-3500m, which belongs to deep buried coal rock reservoirs. The deep coal rock gas resource reserves of this type of coal rock gas reservoir are very rich. In the development process, the drilling cost is high, and in order to improve the single well productivity, the horizontal well + volume fracturing technology is usually used for development. Due to the strong tectonic stress on the coal body, it is easy to form granular structure coal and mylonitic structure coal. The coal rock reservoirs with the above two types of coal body structure are relatively soft, low in strength and poor in permeability, and are not conducive to horizontal well drilling and fracturing reconstruction, which will inevitably lead to poor development effect of coal rock gas reservoirs and reduced productivity. In order to improve the development effect of deep buried coal rock gas reservoirs and strengthen the selection of favorable areas, it is necessary to establish a coal body structure division method which is easy to operate, low in application cost and high in identification accuracy.

[0004] At present, the most commonly used method for the division of coal body structure of coal rock reservoirs can be divided into two types: direct method and indirect method. The direct method is to rely on drilling core observation or to identify based on the image characteristics of micro-resistivity scanning imaging logging data. The above method has high cost, especially in deep buried coal rock reservoirs, because of the increase of well depth, the difficulty of coring and the cost of micro-resistivity scanning imaging logging are greatly increased, which cannot be widely applied. The indirect method is to use conventional logging curves or three-dimensional seismic data to divide the coal body structure. The acquisition cost of three-dimensional seismic data is high, which also cannot be widely applied. Therefore, for the division of coal body structure of deep buried coal rock reservoirs, the comprehensive application of conventional logging curves is particularly important.

[0005] The existing technical methods for dividing the coal body structure by using conventional logging curves mainly include: identifying the coal body structure by using the conventional logging curve intersection method or mathematical algorithms such as clustering analysis, calculating the resistivity or the relative change rate of the hole diameter to identify the coal body structure, or based on the Archie formula, using the change of the pore structure index m to identify the coal body structure. The above methods still have the following problems: 1. The comprehensive application of conventional logging curves is not comprehensive enough, and the types of sensitive logging curves applied in the division of the coal body structure are less, and further integration is lacking; 2. The mathematical algorithms such as clustering analysis need a large number of sample training in the application process, and the application effect is poor in the initial exploration and evaluation process of deep buried coal rock gas. SUMMARY

[0006] In order to overcome the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a coal body structure quantitative division method and application based on logging response mechanism, which can be applied in the initial exploration and evaluation of deep buried coal rock gas reservoir, comprehensively consider multiple conventional logging sensitive curves, perform sensitive information fusion, realize continuous quantitative evaluation of the coal body structure, and improve the division precision of the coal body structure.

[0007] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0008] The present application discloses a coal body structure quantitative division method based on logging response mechanism, comprising the following steps:

[0009] Preliminary identification and division of the coal body structure of the coal rock sample;

[0010] Obtaining logging curve measurement data of different coal body structures, and performing normalization processing on the logging curve measurement data;

[0011] Combining the types of logging curve measurement data, constructing a fragmentation collapse factor and a conductive network factor;

[0012] According to the fragmentation collapse factor and the conductive network factor, the normalized logging curve measurement data is calculated, and according to the calculation result, the division standard of the coal body structure is established.

[0013] Further, the preliminary identification and division of the coal body structure of the coal rock sample are as follows:

[0014] According to the observed damage degree of the coal rock sample, the coal body structure of the coal rock sample is divided into primary structure, fragmentation structure, fragmented structure and mylonitic structure.

[0015] Further, the logging curve measurement data of different coal body structures is obtained, and the logging curve measurement data is normalized as follows:

[0016] The natural potential data, caliper data, deep lateral resistivity curve data, shallow lateral resistivity curve data, acoustic time difference curve data and density curve data of different coal body structures are acquired, and the deep lateral resistivity curve data, shallow lateral resistivity curve data, acoustic time difference curve data and density curve data are normalized.

[0017] Further, the normalization processing formula of the density curve data is as follows:

[0018]

[0019] In the formula, X′ DEN is the normalized density curve data; X DEN is the density curve measurement data.

[0020] Further, the normalization processing formula of the acoustic time difference curve data is as follows:

[0021]

[0022] In the formula, X′ A C is the normalized acoustic time difference curve data; X AC is the acoustic time difference curve measurement data.

[0023] Further, the deep lateral resistivity curve and the shallow lateral resistivity curve adopt a logarithmic normalization method, and are determined based on the following formula:

[0024]

[0025] In the formula, Z′ lg is the logarithmic normalized resistivity curve; Z lg is the resistivity curve; Z min is the minimum value in the coal rock reservoir measurement section logging curve data; Z max is the maximum value in the coal rock reservoir measurement section logging curve data.

[0026] Further, the determination formula of the fragmentation collapse factor is as follows:

[0027]

[0028] In the formula, FR cf is the fragmentation collapse factor; ΔCAL is the abnormal amplitude value of the caliper logging curve; R w is the formation water resistivity; R mf is the flushing zone resistivity; X′ AC is the normalized acoustic time difference logging data; X′ DEN is the normalized density logging data.

[0029] ​The ΔCAL is determined based on the following formula:

[0030] ΔCAL=CAL-Bit

[0031] In the formula, the CAL is the coal reservoir measured section well diameter logging curve data; and the Bit is the coal reservoir section well borehole bit diameter data.

[0032] Further, the determination of the conductive network factor is shown in the following formula:

[0033]

[0034] In the formula, the CO nf is the conductive network factor; the ΔSO is the abnormal amplitude value of the spontaneous potential logging curve; the Z′ RT is the deep lateral resistivity logging data after logarithmic normalization processing; the Z′ RI is the shallow lateral resistivity logging data after logarithmic normalization processing.

[0035] The ΔSP is determined based on the following formula:

[0036] ΔSP=SP-SPP

[0037] In the formula, the SP is the coal reservoir measured section spontaneous potential logging curve data; and the SPP is the coal reservoir adjacent well section spontaneous potential baseline data.

[0038] Further, according to the fragmentation collapse factor and the conductive network factor, the normalized processing logging curve measurement data are calculated, and according to the calculation result, the division standard of the coal body structure is established and is specifically as follows:

[0039] According to the logging curve measurement data of different coal body structures, the fragmentation collapse factors and the conductive network factors corresponding to different coal body structures are calculated, and according to the distribution intervals of the calculation results of the fragmentation collapse factors and the conductive network factors corresponding to different coal body structures, the division standard of different coal body structures according to the fragmentation collapse factors and the conductive network factors is established.

[0040] Based on the above method, the application of the coal body structure quantitative division method based on the logging response mechanism is disclosed, and includes the following steps:

[0041] The logging curve measurement data of the coal body structure of the uncoring well section are acquired;

[0042] According to the division standard of the coal body structure, the fragmentation collapse factor and the conductive network factor are combined with the logging curve measurement data, and the coal body structure of the uncoring well section is divided.

[0043] Compared with the prior art, the application has the following beneficial effects:

[0044] The method of the present application preliminarily identifies and divides the coal body structure of the coal rock sample. The logging curve measurement data of different coal body structures are obtained, and the logging curve measurement data is normalized. The fragmentation collapse factor and the conductive network factor are constructed in combination with the type of the logging curve measurement data. The normalized logging curve measurement data is calculated according to the fragmentation collapse factor and the conductive network factor, and the division standard of the coal body structure is established according to the calculation result. The present application can be applied to the initial exploration evaluation of the deep buried coal rock gas reservoir, the sensitive information fusion is carried out by comprehensively considering multiple conventional logging sensitive curves, the fragmentation collapse factor and the conductive network factor sensitive curve are constructed, the continuous quantitative evaluation of the coal body structure is realized, and the division precision of the coal body structure is improved.

[0045] The application of the coal body structure quantitative division method based on the logging response mechanism of the present application obtains the logging curve measurement data of the coal body structure of the uncoring well section. The coal body structure of the uncoring well section is divided according to the division standard of the coal body structure in combination with the logging curve measurement data by using the fragmentation collapse factor and the conductive network factor. The present application can be applied to the initial exploration evaluation of the deep buried coal rock gas reservoir, the sensitive information fusion is carried out by comprehensively considering multiple conventional logging sensitive curves, the continuous quantitative evaluation of the coal body structure is realized, and the division precision of the coal body structure is improved. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 The method flowchart of the present application is shown in the figure;

[0047] Figure 2 The coal body structure division chart of the embodiment of the present application is shown in the figure;

[0048] Figure 3 The coal rock coring section coal body structure division result and the coal rock coring observation result comparison schematic diagram provided by the optional implementation mode of the present application is shown in the figure;

[0049] Figure 4 The application flowchart of the coal body structure quantitative division method based on the logging response mechanism of the present application is shown in the figure. DETAILED DESCRIPTION

[0050] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0051] It should be noted that the terms "first", "second", and the like in the description and in the claims of the present application and in the above-described drawings are intended to distinguish similar objects and not necessarily describe a particular chronological or sequential order. It should be understood that the data thus used can be interchanged, where appropriate, so that the embodiments of the application described herein can be practiced in other than the order illustrated or described herein. Furthermore, the terms "comprise" and "have", as well as any variations thereof, are intended to cover non-exclusive inclusion, for example, processes, methods, systems, products, or devices that include a series of steps or units are not necessarily limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0052] The present application will be described in further detail below in conjunction with the accompanying drawings:

[0053] Referring to Figure 1 The present application discloses a coal structure quantitative division method based on logging response mechanism, comprising the following steps:

[0054] S1. Preliminary identification and division of coal structure of coal rock samples;

[0055] S2. Obtain logging curve measurement data of different coal structures, and normalize the logging curve measurement data;

[0056] S3. Combined with the type of logging curve measurement data, construct the fragmentation collapse factor and the conductive network factor;

[0057] S4. According to the fragmentation collapse factor and the conductive network factor, calculate the normalized logging curve measurement data, and according to the calculation result, establish the division standard of coal structure.

[0058] Referring to Figure 1In another possible embodiment of the present application, the following is adaptively modified according to the situation. The coal body structure of the coal rock sample is preliminarily identified and divided. The logging curve measurement data of different coal body structures are obtained, and the logging curve measurement data is normalized. In combination with the type of the logging curve measurement data, the fragmentation collapse factor and the conductive network factor are constructed. According to the fragmentation collapse factor and the conductive network factor, the normalized logging curve measurement data is calculated, and according to the calculation result, the division standard of the coal body structure is established. The present application can be applied to the initial exploration and evaluation of the deep buried coal rock gas reservoir, comprehensively considers multiple conventional logging sensitive curves, performs sensitive information fusion, constructs the fragmentation collapse factor and the conductive network factor sensitive curve, realizes the continuous quantitative evaluation of the coal body structure, and improves the division precision of the coal body structure. The problems that the comprehensive application of the conventional logging curve is not comprehensive enough and cannot be effectively applied in the initial exploration and evaluation of the deep buried coal rock gas reservoir in the prior art are solved. The method principle is clear, easy to operate, low in application cost, and high in accuracy of coal body structure identification.

[0059] Embodiment one:

[0060] Referring to Figure 1 The embodiment discloses a coal body structure quantitative division method based on logging response mechanism, comprising the following steps:

[0061] S1. Preliminarily identifying and dividing the coal body structure of the coal rock sample;

[0062] Specifically as follows:

[0063] According to the observed damage degree of the coal rock sample, the coal body structure of the coal rock sample is divided into primary structure, fragmentation structure, granular structure and mylonitic structure.

[0064] S2. Obtaining logging curve measurement data of different coal body structures, and normalizing the logging curve measurement data;

[0065] Specifically as follows:

[0066] The natural potential data, caliper data, deep lateral resistivity curve, shallow lateral resistivity curve, acoustic time difference curve data and density curve data of different coal body structures are obtained, and the deep lateral resistivity curve, shallow lateral resistivity curve, acoustic time difference curve data and density curve data are normalized.

[0067] The normalization processing formula of the density curve data is as follows:

[0068]

[0069] In the formula, X' DEN is the normalized density curve data; X DEN is the density curve measurement data.

[0070] The acoustic travel time curve data difference normalization processing formula is as follows:

[0071]

[0072] In the formula, X A ′ C is the acoustic travel time curve data after normalization processing; X AC is the acoustic travel time curve measurement data.

[0073] The deep lateral resistivity curve and the shallow lateral resistivity curve adopt a logarithmic normalization method and are determined based on the following formula:

[0074]

[0075] In the formula, Z l ′ g is the resistivity curve after logarithmic normalization processing; Z lg is the resistivity curve; Z min is the minimum value in the coal rock reservoir measurement section logging curve data; Z max is the maximum value in the coal rock reservoir measurement section logging curve data.

[0076] S3. A fragmentation collapse factor and a conductive network factor are constructed in combination with the type of logging curve measurement data.

[0077] The determination formula of the fragmentation collapse factor is as follows:

[0078]

[0079] In the formula, FR cf is the fragmentation collapse factor; ΔCAL is the abnormal amplitude value of the caliper logging curve; R w is the formation water resistivity; R mf is the flushing zone resistivity; X′ AC is the acoustic travel time logging data after normalization processing; X′ DEN is the density logging data after normalization processing.

[0080] ΔCAL is determined based on the following formula:

[0081] ΔCAL = CAL-Bit

[0082] In the formula, CAL is the coal rock reservoir measurement section caliper logging curve data; Bit is the coal rock reservoir section wellbore drill bit diameter data of the study area.

[0083] The determination formula of the conductive network factor is as follows:

[0084]

[0085] In the formula, COnf is a conductive network factor; ΔSO is an abnormal amplitude value of the spontaneous potential logging curve; Z' RT is the deep lateral resistivity logging data after logarithmic normalization processing; Z' RI is the shallow lateral resistivity logging data after logarithmic normalization processing.

[0086] ΔSP is determined based on the following formula:

[0087] ΔSP = SP - SPP

[0088] In the formula, SP is the spontaneous potential logging curve data of the coal rock reservoir measurement section; and SPP is the spontaneous potential baseline data of the adjacent well section of the coal rock reservoir.

[0089] S4. According to the fragmentation collapse factor and the conductive network factor, the logging curve measurement data after normalization processing is calculated, and according to the calculation result, the division standard of the coal body structure is established.

[0090] Specifically as follows:

[0091] According to the logging curve measurement data of different coal body structures, the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures are calculated, and according to the distribution interval of the calculation results of the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures, the division standard of different coal body structures according to the fragmentation collapse factor and the conductive network factor is established.

[0092] Referring to Figure 4 , the application further discloses an application of the coal body structure quantitative division method based on the logging response mechanism, which comprises the following steps:

[0093] S1. Obtain the logging curve measurement data of the coal body structure of the uncased well section;

[0094] S2. According to the division standard of the coal body structure, the fragmentation collapse factor and the conductive network factor are used to divide the coal body structure of the uncased well section in combination with the logging curve measurement data.

[0095] Referring to Figure 4 , in another feasible embodiment of the application, the following is adaptively modified according to the situation. Obtain the logging curve measurement data of the coal body structure of the uncased well section. According to the division standard of the coal body structure, the fragmentation collapse factor and the conductive network factor are used to divide the coal body structure of the uncased well section in combination with the logging curve measurement data. The application can be applied to the initial exploration and evaluation of the deep buried coal rock gas reservoir, and the sensitivity information fusion is carried out by comprehensively considering multiple conventional logging sensitive curves, so that the continuous quantitative evaluation of the coal body structure is realized, and the division precision of the coal body structure is improved.

[0096] Embodiment two:

[0097] With a coal rock gas reservoir in a deep buried coal rock gas risk exploration area in a certain basin as an example, the application will be further described in detail in combination with the drawings and specific embodiments.

[0098] Referring to Figure 1 and Figure 4 , the embodiment discloses a coal body structure quantitative division method based on logging response mechanism and application thereof, comprising the following steps:

[0099] S1, identifying and dividing the coal body structure of the coal rock sample.

[0100] According to the coal rock sample obtained by drilling coring in the research area, based on the national standard "GB / T 3005-2013", according to the observed damage degree of the coal rock sample, the coal body structure of the coal rock sample is divided into primary structure, fragmentation structure, granular structure and mylonitic structure.

[0101] S2, obtaining corresponding logging curve measurement data of different coal body structures, the logging curve measurement data including spontaneous potential data SP, caliper data CAL, deep lateral resistivity curve RT, shallow lateral resistivity curve RI, acoustic time difference curve data AC and density curve data DEN, and performing normalization processing on the obtained logging curve measurement data.

[0102] The spontaneous potential data SP, caliper data CAL, deep lateral resistivity curve RT, shallow lateral resistivity curve RI, acoustic time difference curve data AC and density curve data DEN of the coal rock reservoir in the target work area drilling core section are measured by the logging instrument.

[0103] The normalization processing is determined based on the following formula:

[0104] For the density curve DEN normalization processing formula, it is determined based on the following formula:

[0105]

[0106] In the formula, X' DEN is the normalized density curve data; X DEN is the density curve measurement data, and the unit of the density curve measurement data is g / cm 3 .

[0107] For the acoustic time difference curve data AC normalization processing formula, it is determined based on the following formula:

[0108]

[0109] In the formula, X A ' C is the normalized acoustic time difference curve data; X ACThe acoustic travel time curve measurement data, and the unit of the acoustic travel time curve data is μs / ft.

[0110] The log normalization method is adopted for the deep lateral resistivity curve RT and the shallow lateral resistivity curve RI, and the following formula is used for determination:

[0111]

[0112] In the formula, Z l ′ g is the log normalization processed logging curve data; Z lg is the logging curve measurement data; Z min is the minimum value in the coal rock reservoir measurement section logging curve data; Z max is the maximum value in the coal rock reservoir measurement section logging curve data.

[0113] S3, according to the normalized data, a fragmentation collapse factor and a conductive network factor are constructed in combination with response mechanism analysis.

[0114] After the coal body is extruded by tectonic stress, different degrees of tectonic deformation and coal body damage occur, resulting in more developed pores and fissures, smaller coal body strength, and enhanced stress sensitivity, which leads to more prone to wellbore collapse deformation in the drilling process. The above characteristic changes are comprehensively reflected on the conventional logging curves, and the logging response characteristics of different coal body structures can be summarized from two aspects in combination with response mechanism analysis:

[0115] 1. Fragmentation collapse: the higher the degree of coal body structure damage, the more developed the pores and fissures, and the looser the structure, which is prone to cause wellbore collapse and expansion in the drilling process. The higher the fragmentation degree, the more obvious the expansion phenomenon. The above characteristics will lead to abnormal increase of the logging value of the caliper curve, increase of the logging value of the acoustic travel time curve, and decrease of the logging value of the density curve. Since the pore structure index m in the Archie formula can effectively reflect the pore structure of the reservoir, the degree of fissure development will have a significant impact on the size of m. Based on the above response mechanism and the Archie formula, a fragmentation collapse factor is innovatively constructed.

[0116] 2. Conductive network: the coal rock in the target work area is mainly low-rank long-flame coal with high moisture, which has a relatively high resistivity. After the fragmentation of the coal body, the content of small molecules in the coal rock increases, the concentration of free radicals increases, and the water molecules in the coal rock jointly act with the free radicals and small molecules to make the conductive network in the coal rock more developed and the diffusion electromotive force enhanced, thereby respectively leading to decrease of the resistivity of the coal rock, increase of the abnormal amplitude of the spontaneous potential curve logging value, and the coal rock being more prone to mud invasion, which leads to increase of the amplitude difference between the deep and shallow resistivities. Based on the response mechanism, a conductive network factor is constructed.

[0117] The fragmentation collapse factor is determined based on the following formula:

[0118]

[0119] wherein FR cf is the fragmentation collapse factor; ΔCAL is the abnormal amplitude value of caliper logging curve, in; R w is the formation water resistivity, Ω·m; R mf is the flushed zone resistivity, Ω·m; X′ AC is the normalized acoustic travel time logging data; X′ DEN is the normalized density logging data.

[0120] ΔCAL is determined based on the following formula:

[0121] ΔCAL = CAL-Bit

[0122] wherein ΔCAL is the abnormal amplitude value of caliper logging curve, in; CAL is the coal rock reservoir measured section caliper logging curve data, in; Bit is the research area coal rock reservoir section wellbore bit diameter data, in.

[0123] The conductive network factor is determined based on the following formula:

[0124]

[0125] wherein CO nf is the conductive network factor; ΔSP is the abnormal amplitude value of spontaneous potential logging curve, mV; Z′ RT is the logarithm normalized deep lateral resistivity logging data, Ω·m; Z′ RI is the logarithm normalized shallow lateral resistivity logging data, Ω·m.

[0126] ΔSP is determined based on the following formula:

[0127] ΔSP = SP-SPP

[0128] wherein ΔSP is the abnormal amplitude value of spontaneous potential logging curve, mV; SP is the coal rock reservoir measured section spontaneous potential logging curve data, mV; SPP is the coal rock reservoir adjacent well section spontaneous potential baseline data, mV.

[0129] S4, according to the fragmentation collapse factor and the conductive network factor calculation formula, different coal body structures are calculated, and combined with the calculation results, the division standard of different coal body structures is established.

[0130] According to the coal body structure division result of the coal rock sample, the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures are calculated, and the division standard of the fragmentation collapse factor and the conductive network factor for dividing different coal body structures is established according to the distribution interval of the calculation result of the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures, as shown in the following table:

[0131] Table 1, coal body structure division standard:

[0132] Coal body structure CO nf ]] FR cf ]] Primary ＜100 ＜10 Cataclastic ＜100 10-17 Fragmental ＜100 ≥1 7 Mylonitic ≥100 /

[0133] Figure 2 is the coal body structure division chart provided by the optional embodiment of the present application, as shown in Figure 2 , the chart can quickly and effectively divide the coal body structure type of the coal rock reservoir of the non-coring well section.

[0134] S5. Obtain the coal body structure logging curve measurement data of the non-coring well section, and divide the coal body structure of the non-coring well section by using the fragmentation collapse factor and the conductive network factor according to the division standard of the coal body structure and in combination with the logging curve measurement data.

[0135] The logging curve data of the coal rock reservoir section of the target work area measured by the logging instrument is substituted into the fragmentation collapse factor and the conductive network factor calculation formula for operation, and the coal body structure of the target coal rock reservoir is judged according to the following standard:

[0136] When the conductive network factor CO nf of the target coal rock reservoir is <100 and the fragmentation collapse factor FR cf is <10, it is judged that the target coal rock reservoir is a primary structure;

[0137] When the conductive network factor CO nf of the target coal rock reservoir is <100 and the fragmentation collapse factor FR cf is ∈[10, 17], it is judged that the target coal rock reservoir is a fragmentation structure;

[0138] When the conductive network factor CO nf of the target coal rock reservoir is <100 and the fragmentation collapse factor FR cf is ≥17, it is judged that the target coal rock reservoir is a fragmented structure;

[0139] When the conductive network factor CO nf of the target coal rock reservoir is ≥100, it is judged that the target coal rock reservoir is a mylonitic structure.

[0140] Figure 3 is the schematic diagram of the actual application effect provided by the optional embodiment of the present application, as shown in Figure 3 , the chart can quickly and effectively divide the coal body structure type of the coal rock reservoir of the non-coring well section. Figure 3In the figure, the first track is the natural potential data SP and the caliper data CAL, the second track is the depth track, the third track is the lithology profile, the fourth track is the drilling core, the fifth track is the deep lateral resistivity curve RT, the shallow lateral resistivity curve RI and the microspherical focused resistivity curve RXO, the sixth track is the three porosity curves, the seventh track is the lithology volume profile, the eighth track is the calculated fragmentation collapse factor FR cf , the ninth track is the calculated conductive network factor CO nf , the ninth track is the coal body structure division result, and the tenth track is the core photograph corresponding to the coal and rock core section. In the figure, the average value of the conductive network factor CO nf between the depths of 2106.8-2107.5m is 9.9, the fragmentation collapse factor FR cf is 5.8, which is identified as a fragmentation structure, which is consistent with the fragmentation characteristics shown in the tenth track of the coal and rock core photograph. The average value of the conductive network factor CO nf between the depths of 2107.5-2108.0m is 15.1, the fragmentation collapse factor FR cf is 7.3, which is identified as a fragmented structure, which is consistent with the characteristics of severe fragmentation and small particles shown in the tenth track of the coal and rock core photograph. The average value of the conductive network factor CO nf between the depths of 2108.9-2110.0m is 8.0, the fragmentation collapse factor FR cf is 2.4, which is identified as a primary structure, which is consistent with the characteristics of complete coal body and no fragmentation shown in the tenth track of the coal and rock core photograph. By using the logging sensitive parameter curve reconstruction method to divide the coal body structure, the identified coal body structure by the method is consistent with the coal body structure observed by the coal and rock core section, thereby verifying the reliability of the method.

[0141] In summary, the present application provides a coal structure quantitative division method based on logging response mechanism. The method comprises: identifying and dividing the coal structure of coal rock samples; obtaining logging curve measurement data corresponding to different coal structures, wherein the logging curve measurement data comprises spontaneous potential data SP, caliper data CAL, deep lateral resistivity curve RT, shallow lateral resistivity curve RI, acoustic time difference curve data AC and density curve data DEN, and the obtained logging curve measurement data is normalized; combined with response mechanism analysis, the normalized data is used to construct a fragmentation collapse factor and a conductive network factor; different coal structures are calculated according to the fragmentation collapse factor and the conductive network factor calculation formula, and combined with the calculation results, the division standard of different coal structures is established; according to the established coal structure division standard, combined with the logging curve measurement data, the fragmentation collapse factor and the conductive network factor calculation formula are used to realize the division of the coal rock coal structure of the uncased well section. The method has clear principle, is convenient to operate, has low application cost, and has high accuracy in identifying the coal structure.

[0142] The above is only used for describing the technical idea of the present application, and cannot be used to limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A method for quantitatively dividing coal body structure based on logging response mechanism, characterized in that, The method comprises the following steps: Preliminary identification and division of the coal body structure of the coal rock sample; Obtaining logging curve measurement data of different coal body structures, and performing normalization processing on the logging curve measurement data; Combining the types of logging curve measurement data, constructing a fragmentation collapse factor and a conductive network factor; According to the fragmentation collapse factor and the conductive network factor, calculating the normalized logging curve measurement data, and establishing a division standard of the coal body structure according to the calculation result. The determination formula of the fragmentation collapse factor is as follows: In the formula: is a broken-down collapse factor; is an abnormal amplitude value of caliper logging curve; is a formation water resistivity; is a flushing zone resistivity; is acoustic travel time logging data after normalization processing; is density logging data after normalization processing; is determined based on the following equation: In the formula: is the coal reservoir measurement section well bore diameter log curve data; is the coal reservoir section well bore diameter data The determination formula of the conductive network factor is as follows: In the formula: is a conductive network factor; is an abnormal amplitude value of the spontaneous potential logging curve; is deep lateral resistivity logging data after logarithmic normalization processing; is shallow lateral resistivity logging data after logarithmic normalization processing; is determined based on the following equation: In the formula: is the coal rock reservoir measured segment spontaneous potential logging curve data; is the coal rock reservoir adjacent well segment spontaneous potential baseline data.

2. The method of claim 1, wherein the method is characterized by, The preliminary identification and division of the coal body structure of the coal rock sample are as follows: According to the observed damage degree of the coal rock sample, the coal body structure of the coal rock sample is divided into primary structure, fragmentation structure, granular structure and mylonitic structure.

3. The method of claim 1, wherein the method is characterized by, The normalization processing of the logging curve measurement data of different coal body structures is as follows: Obtaining natural potential data, caliper data, deep lateral resistivity curve, shallow lateral resistivity curve, acoustic travel time curve data and density curve data of different coal body structures, and performing normalization processing on the deep lateral resistivity curve, shallow lateral resistivity curve, acoustic travel time curve data and density curve data.

4. The method of claim 3, wherein the method is characterized by, The normalization processing formula of the density curve data is as follows: In the formula: is the normalized density curve data; is the density curve measurement data.

5. The method of claim 3, wherein the method is characterized by: The normalization processing formula of the acoustic travel time curve data is as follows: In the formula: is the normalized acoustic traveltime curve data; is the acoustic traveltime curve measurement data.

6. The method of claim 3, wherein the method is characterized by, The deep lateral resistivity curve and the shallow lateral resistivity curve adopt a logarithmic normalization method, and are determined based on the following formula: In the formula: is a resistivity curve after logarithmic normalization processing; is a resistivity curve; is a minimum value in the coal rock reservoir measurement section logging curve data; is a maximum value in the coal rock reservoir measurement section logging curve data.

7. The method of claim 1, wherein the method is characterized by: The calculation of the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures according to the logging curve measurement data of different coal body structures, and the establishment of the division standard of different coal body structures according to the distribution interval of the calculation results of the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures are as follows: According to the logging curve measurement data of different coal body structures, calculating the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures, and establishing a division standard of different coal body structures according to the distribution interval of the calculation results of the fragmentation collapse factor and the conductive network factor corresponding to different coal body structures.

8. The use of a method for quantitative division of coal structure based on logging response mechanism according to any one of claims 1 to 7, characterized in that, The method comprises the following steps: Obtaining logging curve measurement data of the coal body structure of a coring-free well section; According to the division standard of the coal body structure, combining the logging curve measurement data, and using the fragmentation collapse factor and the conductive network factor to divide the coal body structure of the coring-free well section.

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