Method and system for identifying spatial morphology of hot dry rock fracturing transformation

Abstract

The present invention provides a method and system for identifying the spatial morphology of hot dry rock fracturing transformation, which determines electromagnetic method parameters by forward numerical simulation, obtains the original data of the background field before fracturing transformation and the original data of the abnormal field after fracturing transformation by laying a ground measurement network, determines the relative electromagnetic anomaly value distribution before and after fracturing transformation based on the original data of the background field and the original data of the abnormal field, and determines the spatial morphology of fracturing transformation based on the relative electromagnetic anomaly value distribution. The present invention can alleviate the technical problems of weak anti-interference ability, limited detection depth, insufficient detection accuracy, and poor construction flexibility existing in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of geophysical exploration technology, and in particular to a method and system for identifying the spatial morphology of hot dry rock fracturing transformation. Background Art

[0002] Artificial reservoir creation is a method commonly used in the development of resources such as oil, natural gas, shale gas, and geothermal (hot dry rock). The method is to inject a large amount of high-pressure liquid into the target area, and transform the reservoir fracture structure through hydraulic fracturing, forming one or more main fractures while expanding natural fractures or secondary fractures. At the same time, secondary fractures continue to branch out to form secondary secondary fractures and more levels of secondary fractures, forming a fracture network in which natural fractures and artificial fractures are intertwined, thereby increasing the seepage area and conductivity, and improving the recovery rate and heat exchange rate.

[0003] A deep understanding of the geometry and extension of small hydraulic fracturing cracks is crucial to improving the effect of hydraulic fracturing and production enhancement operations in low-permeability hot dry rock, improving the connectivity of hot dry rock wells and increasing the heat exchange rate. During the hydraulic fracturing process, low-resistivity fracturing fluid migrates and fills in the gaps and reformed spaces of high-resistivity reservoirs, causing changes in reservoir resistivity, which provides a physical basis for electromagnetic monitoring. Compared with microseismic, electromagnetic monitoring is more intuitive in depicting the migration direction, migration channels and enrichment areas of fracturing fluids, and has unique advantages. Therefore, it is a more effective means to use electromagnetic methods for fluid migration monitoring in hot dry rock development projects such as hydraulic fracturing.

[0004] In hot dry rock well construction areas where human activities, mechanical vibrations and power interference are serious, it is difficult to obtain high-quality monitoring data when using traditional electromagnetic methods to detect targets such as original or hydraulically fractured cracks in hot dry rock reservoirs. There are limitations such as weak anti-interference ability, limited detection depth, and insufficient detection accuracy. Although the well-ground or inter-well electromagnetic method has high detection accuracy, it is easily affected by high temperature and high pressure well conditions, well depth, well diameter, cementing technology and casing material, and it is impossible to flexibly adjust the monitoring range, monitoring cycle and collection method. There are certain construction risks and uncertainties, and the cost is much higher than ground monitoring. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method and system for identifying the spatial morphology of hot dry rock fracturing transformation, so as to alleviate the technical problems existing in the prior art, such as weak anti-interference ability, limited detection depth, insufficient detection accuracy and poor construction flexibility.

[0006] In a first aspect, an embodiment of the present invention provides a method for identifying the spatial morphology of hot dry rock fracturing transformation, comprising: determining electromagnetic parameters of the area to be measured based on a forward simulation result obtained by performing forward numerical simulation on the area to be measured; wherein the electromagnetic parameters include: point spacing, electrode spacing, transceiver spacing, supply electrode spacing, supply current, excitation waveform, excitation frequency and single frequency excitation cycle number; based on a ground measuring network arranged in the area to be measured, obtaining the original data of the area to be measured before the injection of fracturing fluid, and obtaining background field original data; wherein the original data includes: the excitation frequency of each measuring point in the ground measuring network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point; based on the ground measuring network arranged in the area to be measured, obtaining the original data of the area to be measured after the injection of fracturing fluid, and obtaining abnormal field original data; based on the background field original data and the abnormal field original data, determining the relative electromagnetic anomaly value distribution of the area to be measured before and after the injection of fracturing fluid; based on the relative electromagnetic anomaly value distribution, determining the fracturing transformation spatial morphology of the area to be measured.

[0007] As a possible implementation, the step of determining the electromagnetic parameters of the area to be tested based on the forward modeling results obtained by performing forward numerical simulation on the area to be tested includes: establishing a geological resistivity model of the area to be tested based on the well logging geological stratification data, well logging segmentation data and well logging resistivity data of each segment of the area to be tested; based on the geological resistivity model, performing forward numerical simulation on the area to be tested using the electromagnetic method to obtain forward simulation results; wherein the forward simulation results include simulated electromagnetic data of the area to be tested before the injection of fracturing fluid, and simulated electromagnetic data of the area to be tested after the injection of fracturing fluid; and determining the electromagnetic parameters based on the forward simulation results.

[0008] As a possible implementation, the relative electromagnetic anomaly value distribution of the test area before and after the injection of fracturing fluid includes the relative amplitude anomaly distribution of the test area in different time periods before and after the injection of fracturing fluid; based on the background field original data and the abnormal field original data, the step of determining the relative electromagnetic anomaly value distribution of the test area before and after the injection of fracturing fluid includes: preprocessing the background field original data and the abnormal field original data to obtain amplitude data of different frequencies of the test area before and after the injection of fracturing fluid; wherein the preprocessing includes at least one of the following: filtering, superposition, Fourier transform and current normalization; based on the amplitude data of a specified frequency before and after the injection of fracturing fluid, determining the relative amplitude anomaly distribution of the test area in different time periods before and after the injection of fracturing fluid.

[0009] As a possible implementation, after the step of preprocessing the background field raw data and the abnormal field raw data to obtain the amplitude data of different frequencies of the test area before and after the injection of fracturing fluid, the method further includes: inverting the amplitude data of different frequencies of the test area before and after the injection of fracturing fluid to obtain the inverted resistivity data of the test area at different times before and after the injection of fracturing fluid; based on the inverted resistivity data of the test area at different times before and after the injection of fracturing fluid, respectively drawing the inverted resistivity profile of the test area within a specified time period before and after the injection of fracturing fluid, the inverted resistivity slice diagram of different depths of the test area within a specified time period before and after the injection of fracturing fluid, and the total longitudinal conductivity plane diagram of the test area at different times before and after the injection of fracturing fluid.

[0010] As a possible implementation, the step of establishing a geological resistivity model of the area to be measured based on the logging geological stratification data, the logging segmentation data and the logging resistivity data of each segment of the area to be measured includes: calculating the measured vertical conductivity data of each segment of the logging based on the thickness of each geologically divided layer and the measured resistivity value of each layer in the logging geological stratification data; establishing an initial model based on the thickness of each geologically divided layer and the mean rock lithology resistivity of each layer in the logging geological stratification data, and calculating the vertical conductivity data of each layer in the initial model; respectively drawing a first total longitudinal conductivity curve of the real formation and a second total longitudinal conductivity curve of the model formation, and adjusting the size of the mean rock lithology resistivity until the deviation between the second total longitudinal conductivity curve and the first total longitudinal conductivity curve is within a preset range, thereby obtaining the geological resistivity model.

[0011] As a possible implementation, based on the geological resistivity model, the electromagnetic method is used to perform forward numerical simulation on the area to be tested to obtain the forward simulation result, including: establishing a fracture model of the area to be tested based on the geological resistivity model and preliminary judgment information obtained in advance; wherein the preliminary judgment information includes: fracture scale, fracture angle, fracture morphology, fracture burial depth, fracture water richness and fracturing fluid resistivity; based on the fracture model, the electromagnetic method is used to perform forward numerical simulation on the area to be tested to obtain the forward simulation result.

[0012] As a possible implementation, the step of determining the fracturing transformation spatial morphology of the area to be tested based on the relative electromagnetic anomaly value distribution includes: determining the resistivity residual abnormal data of the area to be tested within a specified time period before and after the injection of fracturing fluid based on the inverted resistivity data of the area to be tested at different times before and after the injection of fracturing fluid; drawing a single-section resistivity residual abnormal map of the area to be tested within the specified time period before and after the injection of fracturing fluid and resistivity residual slice maps of different depths in the area to be tested within the specified time period before and after the injection of fracturing fluid based on the resistivity residual abnormal data of the area to be tested within the specified time period before and after the injection of fracturing fluid; drawing a three-dimensional resistivity residual abnormal map of the area to be tested within the specified time period before and after the injection of fracturing fluid based on the single-section resistivity residual abnormal map of the area to be tested within the specified time period before and after the injection of fracturing fluid and the resistivity residual slice maps of different depths in the area to be tested within the specified time period before and after the injection of fracturing fluid; the three-dimensional resistivity residual abnormal map represents the fracturing transformation spatial morphology of the area to be tested within the specified time period.

[0013] In a second aspect, an embodiment of the present invention further provides a system for identifying the spatial morphology of hot dry rock fracturing transformation, comprising: a first determination module, for determining the electromagnetic parameters of the area to be measured based on the forward simulation results obtained by performing forward numerical simulation on the area to be measured; wherein the electromagnetic parameters include: point spacing, electrode spacing, transceiver spacing, supply electrode spacing, supply current, excitation waveform, excitation frequency and number of single-frequency excitation cycles; a first acquisition module, for acquiring the original data of the area to be measured before the injection of fracturing fluid based on the ground measurement network deployed in the area to be measured, and obtaining the background field original data; wherein the original data packet The invention comprises: the excitation frequency of each measuring point in the ground measuring network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point; a second acquisition module is used to acquire the original data of the area to be measured after the injection of fracturing fluid based on the ground measuring network arranged in the area to be measured, so as to obtain the original data of the abnormal field; a second determination module is used to determine the relative electromagnetic abnormal value distribution of the area to be measured before and after the injection of fracturing fluid based on the background field original data and the abnormal field original data; a third determination module is used to determine the fracturing transformation spatial morphology of the area to be measured based on the relative electromagnetic abnormal value distribution.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for identifying the spatial morphology of hot dry rock fracturing transformation when executing the computer program.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the above-mentioned method for identifying the spatial morphology of hot dry rock fracturing transformation.

[0016] The embodiment of the present invention provides a method and system for identifying the spatial morphology of hot dry rock fracturing transformation, which determines the electromagnetic method parameters by forward numerical simulation, obtains the original data of the background field before fracturing transformation and the original data of the abnormal field after fracturing transformation by laying a ground measurement network, determines the relative electromagnetic anomaly value distribution before and after fracturing transformation based on the original data of the background field and the original data of the abnormal field, and determines the spatial morphology of fracturing transformation based on the relative electromagnetic anomaly value distribution. The above technology can alleviate the technical problems of weak anti-interference ability, limited detection depth, insufficient detection accuracy, and poor construction flexibility in the prior art.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of a flow chart of a method for identifying the spatial morphology of hot dry rock fracturing transformation in an embodiment of the present invention;

[0021] Figure 2 This is an example diagram of a geological resistivity model in an embodiment of the present invention;

[0022] Figure 3 This is an example diagram of a single horizontal plate-shaped body model in an embodiment of the present invention;

[0023] Figure 4 This is an example diagram of a single vertical plate-shaped body model in an embodiment of the present invention;

[0024] Figure 5 This is an example diagram of a multi-plate body model in an embodiment of the present invention;

[0025] Figure 6 This is an example diagram of an irregular complex model in an embodiment of the present invention;

[0026] Figure 7 An example diagram of electromagnetic method parameters in an embodiment of the present invention;

[0027] Figure 8 This is an example diagram of a ground monitoring network in an embodiment of the present invention;

[0028] Fig. 9 This is an example diagram of relative amplitude anomalies of different acquisition methods under a square grid measurement network in an embodiment of the present invention;

[0029] Fig.10 This is an example diagram of relative amplitude anomalies of different acquisition modes under a ring-shaped measurement network in an embodiment of the present invention;

[0030] Fig.11 It is a schematic diagram of the inversion resistivity profile of the same measuring line before and after fracturing in a certain annual interval acquisition mode in an embodiment of the present invention;

[0031] Fig.12 This is an example diagram of inverted resistivity slice diagrams at different depths in a certain annual interval acquisition mode in an embodiment of the present invention;

[0032] Fig.13 It is a total longitudinal conductivity plane diagram at a certain time after fracturing in the interval acquisition mode of the area to be tested in a certain year in the embodiment of the present invention;

[0033] Fig.14 It is a profile resistivity residual anomaly diagram of the area to be measured in a certain year under the interval acquisition mode in the embodiment of the present invention;

[0034] Fig.15 It is a resistivity residual slice diagram at different depths in the interval acquisition mode of the area to be tested in a certain year in an embodiment of the present invention;

[0035] Fig.16 It is a three-dimensional resistivity residual anomaly diagram before and after fracturing fluid in the interval acquisition mode of the area to be tested in a certain year in the embodiment of the present invention;

[0036] Fig.17 It is a schematic flow chart of another method for identifying the spatial morphology of hot dry rock fracturing transformation in an embodiment of the present invention;

[0037] Fig.18 It is a structural schematic diagram of a hot dry rock fracturing transformation space morphology recognition system in an embodiment of the present invention;

[0038] Fig.19 It is a structural schematic diagram of another system for identifying the spatial morphology of hot dry rock fracturing and transformation in an embodiment of the present invention;

[0039] Fig. 20 The figure is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described in combination with the embodiments below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] At present, in the construction area of ​​hot dry rock wells with serious human activities, mechanical vibration and power interference, it is difficult to obtain high-quality monitoring data when the traditional electromagnetic method detects the original or hydraulic fracturing small cracks in the hot dry rock reservoir, and has limitations such as weak anti-interference ability, limited detection depth, and insufficient detection accuracy; although the electromagnetic method between the well and the ground or between wells has a high detection accuracy, it is easily affected by the high temperature and high pressure well conditions, well depth, well diameter, cementing process and casing material, and cannot flexibly adjust the monitoring range, monitoring cycle and collection method. There are certain construction risks and uncertainties, and the cost is much higher than ground monitoring. Based on this, the implementation of the present invention provides a method and system for identifying the spatial morphology of hot dry rock fracturing transformation, which can alleviate the technical problems of weak anti-interference ability, limited detection depth, insufficient detection accuracy and poor construction flexibility in the prior art.

[0042] To facilitate understanding of this embodiment, a method for identifying the spatial morphology of hot dry rock fracturing transformation disclosed in an embodiment of the present invention is first described in detail. Figure 1 A schematic flow chart of a method for identifying the spatial morphology of hot dry rock fracturing transformation is shown, and the method may include the following steps:

[0043] Step S102, based on the forward simulation results obtained by performing forward numerical simulation on the area to be measured, the electromagnetic parameters of the area to be measured are determined; wherein the electromagnetic parameters include: point spacing, electrode spacing, transmitting and receiving spacing, supply electrode spacing, supply current, excitation waveform, excitation frequency and single frequency excitation cycle number.

[0044] Step S104, based on the ground measuring network deployed in the area to be measured, the original data of the area to be measured before the fracturing fluid is injected is obtained to obtain the background field original data; wherein the original data includes: the excitation frequency of each measuring point in the ground measuring network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point.

[0045] Step S106, based on the ground measurement network deployed in the area to be measured, the original data of the area to be measured after the fracturing fluid is injected is obtained to obtain the original data of the abnormal field.

[0046] Step S108, based on the background field original data and the abnormal field original data, determine the relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid.

[0047] Step S110, determining the spatial form of the hydraulic fracturing in the area to be tested based on the relative electromagnetic anomaly value distribution.

[0048] The embodiment of the present invention provides a method for identifying the spatial morphology of hot dry rock fracturing transformation, which determines the electromagnetic method parameters by forward numerical simulation, obtains the original data of the background field before the fracturing transformation and the original data of the abnormal field after the fracturing transformation by laying a ground measurement network, determines the relative electromagnetic anomaly value distribution before and after the fracturing transformation based on the original data of the background field and the original data of the abnormal field, and determines the spatial morphology of the fracturing transformation based on the relative electromagnetic anomaly value distribution. The above technology can alleviate the technical problems of weak anti-interference ability, limited detection depth, insufficient detection accuracy, and poor construction flexibility in the prior art.

[0049] As a possible implementation, the above step S102 (i.e., determining the electromagnetic parameters of the area to be measured based on the forward simulation results obtained by performing forward numerical simulation on the area to be measured) may include the following operation modes:

[0050] (11) A geological resistivity model of the area to be tested is established based on the well logging geological stratification data, well logging segmentation data and well logging resistivity data of each segment of the area to be tested.

[0051] Specifically, based on the thickness of each geologically divided layer in the well logging geological stratification data and the measured resistivity value of each layer, the measured longitudinal conductivity data of each section of the well logging can be calculated; based on the thickness of each geologically divided layer in the well logging geological stratification data and the average value of the rock lithology resistivity of each layer, an initial model is established, and the longitudinal conductivity data of each layer in the initial model is calculated; the first total longitudinal conductivity curve of the real formation and the second total longitudinal conductivity curve of the model formation are respectively drawn, and the size of the average value of the rock lithology resistivity is adjusted until the deviation between the second total longitudinal conductivity curve and the first total longitudinal conductivity curve is within a preset range, thereby obtaining the above-mentioned geological resistivity model.

[0052] Schematically, for example, the logging geological stratification data, logging segmentation data and the resistivity data of each segment of the logging are collected; then, the thickness h of each geological layer divided in the logging geological stratification data is calculated. rel And the measured resistivity value of each layer ρ rel , the following formula is used to calculate the measured vertical conductivity data of each section of the well logging:

[0053] S rel i =h rel i / ρrel i ;

[0054] Among them, h rel i is the thickness of the i-th layer of the well logging, ρ rel i is the measured resistivity value of the i-th layer in the well logging, S rel i is the measured vertical conductivity value of the i-th layer in the well logging;

[0055] The thickness of each layer h based on the geological division in the well logging geological stratification data mol and the mean resistivity of each layer of rock ρ mol , see Figure 2 (a) and Figure 2 As shown in (c), a rectangular coordinate system with resistivity as the horizontal axis and depth as the vertical axis is established, and a first resistivity curve of depth with respect to the measured resistivity and a second resistivity curve of depth with respect to the mean value of rock lithology resistivity are respectively plotted in the rectangular coordinate system. The second resistivity curve is the above-mentioned initial model. Then, the longitudinal conductivity data of each layer in the initial model is calculated using the following formula:

[0056] S mol i =h mol i / ρ mol i ;

[0057] Among them, h mol i is the thickness of the i-th layer of the model (same as the thickness of the i-th layer of the well logging h rel i same), mol i is the resistivity value of the i-th layer of the model, S mol i is the model longitudinal conductance value of the i-th layer of the model;

[0058] A rectangular coordinate system with longitudinal conductivity as the horizontal axis and depth as the vertical axis is established, and a curve of depth with respect to the measured longitudinal conductivity value (i.e., the first total longitudinal conductivity curve) and a curve of depth with respect to the model longitudinal conductivity value (i.e., the second total longitudinal conductivity curve) are respectively plotted in the rectangular coordinate system, see Figure 2 (b); then the mean rock resistivity ρ is continuously adjusted mol (the mean value should be within the statistical interval of the lithological resistivity of the formation) until the deviation between the second total longitudinal conductivity curve and the first total longitudinal conductivity curve is within the preset range. At this time, the corresponding second resistivity curve (i.e., the above initial model) is the above geological resistivity model, so that Figure 2The two curves in (b) are overlapped as much as possible to make the established geological resistivity model as close to the actual stratum as possible.

[0059] (12) Based on the geological resistivity model, the electromagnetic method is used to perform forward numerical simulation on the test area to obtain forward simulation results; wherein the forward simulation results include simulated electromagnetic data of the test area before the injection of fracturing fluid, and simulated electromagnetic data of the test area after the injection of fracturing fluid.

[0060] Specifically, a fracture model of the area to be tested can be established based on the above-mentioned geological resistivity model and the preliminary judgment information obtained in advance; wherein the preliminary judgment information includes: fracture scale, fracture angle, fracture morphology, fracture burial depth, fracture water richness and fracturing fluid resistivity; based on the fracture model, the electromagnetic method is used to perform forward numerical simulation on the area to be tested to obtain the above-mentioned forward simulation results.

[0061] The above forward numerical simulation can adopt staggered sampling finite difference, finite volume method, unstructured grid vector finite element method, etc. The specific method can be selected according to actual needs and is not limited to this.

[0062] Schematically, for example, refer to Figure 3 (a) Figure 4 (a) Figure 5 (a) and Figure 6 As shown in (a), using the established geological resistivity model and combining the above preliminary judgment information, multiple uniform layered two-dimensional / three-dimensional fracture models are established. Figure 3 (a) is a single horizontal plate model, which is used to simulate a low-resistance horizontal fracture cluster with a high degree of water enrichment. The direction in which the hot dry rock well extends downward is the Z-axis direction. The resistivity of the fracture cluster (i.e., the horizontal plate, also known as the anomaly) is 10Ω·m. The geometric dimensions of the horizontal plate are 30m(x)×50m(y)×20m(z). The center of the fracture cluster is buried at a depth of 3910m, and the hot dry rock well is located 100m away from the anomaly. Figure 4 (a) is a single vertical plate model simulating a low-resistance vertical fracture cluster with a high degree of water enrichment. The resistivity of the fracture cluster (i.e., vertical plate, also known as anomaly) is 10Ω·m, the geometric dimensions of the vertical plate are 20m(x)×30m(y)×50m(z), the central position is buried at a depth of 3910m, and the hot dry rock well is 100m away from the anomaly. Figure 5(a) is a multi-plate model, which is used to simulate fracture clusters. It is used to simulate low-resistance fracture clusters with high water-richness (resistivity of 10Ω·m) and medium-resistance fracture clusters with low water-richness (resistivity of 500Ω·m). 100m to the left of the hot dry rock well, two low-resistance fracture clusters with geometric dimensions of 20m(x)×50m(y)×10m(z) and one medium-resistance fracture cluster with geometric dimensions of 20m(x)×50m(y)×10m(z) are closely arranged up and down to form a geometric dimension of 20m(x)×50m(y)×10m(z). ×50m(y)×30m(z), and the medium-resistance fracture cluster is located between two low-resistance fracture clusters; 100m to the right of the hot dry rock well, two low-resistance fracture clusters with geometric dimensions of 20m(x)×30m(y)×10m(z) and one medium-resistance fracture cluster with geometric dimensions of 10m(x)×30m(y)×10m(z) are closely arranged on the left and right to form a combination with geometric dimensions of 50m(x)×30m(y)×10m(z), and the medium-resistance fracture cluster is located between the two low-resistance fracture clusters. Figure 6 (a) is an irregular complex model, which is used to simulate low-resistance fracture clusters with high water-richness (resistivity of 10Ω·m). Within 100m on the left side of the hot dry rock well are fracture clusters with different intervals, the top opening thickness is 30m, the thickness of each cluster bifurcation point is 20m, the vertical intervals of horizontal fracture segments are 10m and 20m, and the extension length of each cluster is 50m; within 100m on the right side of the hot dry rock well are fracture clusters with different angles, the top opening thickness is 30m, the thickness of each cluster bifurcation point is 20m, the fracture segment bifurcation angles are 30° and 60°, and the extension length of each cluster is 50m.

[0063] refer to Figure 3 (b) Figure 4 (b) Figure 5 (b) and Figure 6 As shown in (b), one of the four fracture models or a combination of multiple models in the four fracture models is used to carry out forward numerical simulation of the test area, and the corresponding forward simulation diagram is drawn to obtain the above forward simulation results; wherein, Figure 3 (b) is the forward simulation diagram of a single horizontal plate model in the Y-axis direction and the Z-axis direction. Different colors are used to represent different resistivity intervals in the forward simulation diagram. Figure 4 (b) is the forward simulation diagram of a single vertical plate model in the Y-axis direction and the Z-axis direction. Different colors are used to represent different resistivity ranges in the forward simulation diagram. Figure 5 (b) is the forward simulation diagram corresponding to the multi-plate model, in which different colors are used to represent different resistivity intervals; Figure 6(a) is the forward simulation diagram corresponding to the irregular complex model. Different colors are used to represent different resistivity ranges in the forward simulation diagram. The forward numerical simulation of the fracture model can accurately locate the abnormal bodies of different sizes. The morphology of the abnormal bodies is basically consistent with the model, which proves that electromagnetic monitoring combined with forward numerical simulation can effectively identify small fracture clusters.

[0064] (13) Determine the electromagnetic parameters based on the forward simulation results.

[0065] refer to Figure 7 , combined with the forward simulation diagram, the total amount of injected fracturing fluid and the plane distribution range of microseismic events, the electromagnetic parameters of the area to be measured are determined; wherein the electromagnetic parameters include but are not limited to point spacing, observation component, transmitting and receiving distance, electrode spacing length, power supply current, supply electrode spacing (AB), excitation waveform, excitation cycle, number of single frequency excitation cycles, number of measuring points, electrode resistance, transmitting resistance, etc.

[0066] As a possible implementation, the above steps S104 to S106 may include the following operation modes:

[0067] (21) An excitation source is arranged in the area to be tested so as to continuously emit pulse excitation current into the ground through the excitation source and generate induced eddy current in the ground.

[0068] The above-mentioned excitation source can adopt a high-power excitation device capable of emitting multi-frequency excitation signals. The specific device can be selected according to actual needs and is not limited to this. According to the electromagnetic method parameters determined in the above-mentioned step S102, a high-power excitation device capable of emitting multi-frequency excitation signals can be arranged at a suitable position in the area to be measured as the above-mentioned excitation source. The excitation source continuously emits a high-power pulse excitation current to the ground through the grounding electrode, and excites an induced electromagnetic field underground, so that the underground medium generates induced eddy currents, and the induced eddy currents gradually diffuse and decay to the underground half space. The diffusion speed and the attenuation amplitude are related to the conductivity of the underground medium.

[0069] (22) Before injecting fracturing fluid into the area to be tested, a ground measuring network is laid out in the middle area of ​​the excitation source coverage range in the area to be tested, with the location of the fracturing well in the area to be tested as the center; wherein the ground measuring network is a grid-shaped measuring network or a ring-shaped measuring network.

[0070] For example, see Figure 8 As shown, before injecting fracturing fluid into the area to be tested, the above-mentioned ground measuring network is arranged with the ground projection of the bottom of the hot dry rock fracturing well as the center. The ground measuring network can adopt a grid measuring network (with Figure 8 The left half of the network) or a ring network (with Figure 8 The monitoring area can be flexibly adjusted according to the trajectory of the hot dry rock fracturing well and the construction progress; the ground measurement network includes multiple measurement lines ( Figure 8 Indicated by solid lines) and multiple measuring points ( Figure 8 All measuring points are determined by real-time differential positioning and clearly marked. The direction of the survey line is generally perpendicular to the main structural direction of the site. The point distance (i.e. the distance between the measuring points) can be taken in the range of 10 to 50 m according to the depth and scale of the cracks. The electrode distance can be flexibly adjusted according to needs, and can be selectively encrypted in key monitoring areas (i.e., more measuring points are added). Real-time differential positioning must ensure that the survey line direction, measuring point location, electrode distance and design error do not exceed 1%, and the survey line number and measuring point number are clearly marked.

[0071] As a specific example, in order to further ensure the accuracy of data acquisition, the connection direction of the two power supply electrodes of the excitation source is parallel to the survey line, or the angle between the connection direction of the two power supply electrodes of the excitation source and the survey line is not greater than 1°; the horizontal distance between the survey line closest to the excitation source and the excitation source is not less than 5km, and the distance between the two power supply electrodes is not less than 4km; the excitation waveform is a square wave with a duty cycle of 1 and not exceeding zero, and the excitation frequency must ensure that the required monitoring depth is reached. The number of frequencies can be encrypted at the depth of the fracturing section as needed to ensure the vertical resolution; the area of ​​the power supply electrode of the excitation source is increased, and multiple cables are connected in parallel to reduce the grounding resistance to ensure the energy intensity of the excitation source, so that the power supply current is not less than 70A, and the square wave signal of a single excitation frequency is repeated for not less than 30 times, and a high-power constant current generator set and a constant current time-frequency electromagnetic transmitter are required to ensure that the power supply current and the excitation frequency are consistent in different time periods.

[0072] (23) Collect the horizontal induced electric field component data of the induced eddy current in the test area before the fracturing fluid is injected to obtain the original data of the background field.

[0073] Before injecting fracturing fluid into the area to be tested, the data acquisition station can be used to collect the horizontal induced electric field component data generated by the changes in the above-mentioned induced eddy current in the area where the ground measurement network is located to obtain the above-mentioned background field original data; this step is repeated at least twice to ensure that a high signal-to-noise ratio electromagnetic signal is obtained.

[0074] (24) Collecting horizontal induced electric field component data of the induced eddy current in the test area after the fracturing fluid is injected to obtain the abnormal field original data.

[0075] After injecting fracturing fluid into the area to be tested, the data acquisition station can be used to collect the horizontal induced electric field component data generated by the changes of the induced eddy current in the area where the ground measuring network is located to obtain the above-mentioned abnormal field original data.

[0076] When collecting the above-mentioned background field raw data and the above-mentioned abnormal field raw data, two collection methods can be used, namely continuous collection and interval collection; continuous collection is to collect data every day after fracturing, and interval monitoring is to collect data after a certain fracturing process is completed; the two collection methods are completed in the surrounding area of ​​the same hot dry rock fracturing well in different years, and the excitation source position, power supply electrode position, measurement network range and measurement point position of the two collection methods should remain completely consistent. The above-mentioned continuous collection method and interval collection method can be flexibly adjusted according to the fracturing monitoring needs and funding budget, and there is no limitation on this; among them, when using the interval collection method, if the excitation source needs to be retrieved and deployed again, a clear mark should be set up at the power supply electrode.

[0077] In order to further reduce the impact of mechanical vibration on monitoring data, the above-mentioned two methods of continuous monitoring and interval monitoring can flexibly adjust the collection time period according to the pause intervals of on-site construction, and construction can be carried out during the day or at night; the collection station number and the measuring point number must correspond one by one, and records must be kept to ensure that the same collection station is used for data collection at the same measuring point when collecting data at different time periods; if the number of collection stations is not enough to cover the entire ground monitoring network at the same time, the method of multiple excitation sources and simultaneous collection of multiple groups of collection stations should be adopted.

[0078] As a possible implementation, the relative electromagnetic anomaly value distribution of the test area before and after the injection of the fracturing fluid may include the relative amplitude anomaly distribution of the test area in different time periods before and after the injection of the fracturing fluid; based on this, the above step S108 (i.e., determining the relative electromagnetic anomaly value distribution of the test area before and after the injection of the fracturing fluid based on the background field original data and the abnormal field original data) may include the following operation modes:

[0079] (31) The background field raw data and the abnormal field raw data are preprocessed to obtain the amplitude data of different frequencies in the test area before and after the injection of fracturing fluid.

[0080] The above preprocessing includes but is not limited to: filtering, superposition, Fourier transform and current normalization.

[0081] Specifically, the background field raw data and the abnormal field raw data can be filtered, and then the filtered background field raw data and the abnormal field raw data can be superimposed and Fourier transformed to obtain the real and imaginary components and coordinate data of different frequencies of all measuring points of the ground measuring network, and the real and imaginary components and coordinate data of the emission current; the obtained data can be subjected to current normalization processing to obtain the amplitude and phase data of different frequencies of the measured area before and after the injection of fracturing fluid;

[0082] (32) Based on the amplitude data of the specified frequency in the test area before and after the injection of the fracturing fluid, the relative amplitude abnormal distribution in different time periods before and after the injection of the fracturing fluid in the test area is determined.

[0083] Specifically, the amplitude and phase data of different frequencies before and after the injection of fracturing fluid can be used to select a frequency (i.e., the above-mentioned specified frequency) suitable for the target (i.e., the spatial cracks of the fracturing transformation) burial depth, and the relative amplitude abnormal data of the test area in different time periods before and after the injection of fracturing fluid can be calculated using the following formula:

[0084]

[0085] Among them, A relative is the relative amplitude anomaly, A1 is the electric field amplitude before the injection of fracturing fluid, B i is the electric field amplitude after the fracturing fluid is injected in the i-th section;

[0086] Using the calculated relative amplitude anomaly data of the test area in different time periods before and after the injection of fracturing fluid, the relative amplitude anomaly distribution map of the test area at different times before and after the injection of fracturing fluid is drawn. The negative anomaly (i.e., the relative amplitude anomaly is a negative value) characterizes the migration direction of the fracturing fluid and the crack filling situation. The smaller the negative value, the richer the fracturing fluid and the better the crack connectivity. Relevant personnel can preliminarily determine the location of artificial reservoir fractures based on the relative anomaly distribution map of different time periods, thereby achieving the purpose of quickly detecting artificial reservoir fractures.

[0087] For example, see Fig. 9 As shown, Fig. 9 (a) and (b) are the relative amplitude anomaly diagrams of two adjacent acquisition times under the continuous acquisition mode of the grid network in a certain year. Different colors are used to represent different relative amplitude anomaly intervals in the relative amplitude anomaly diagram. Because the acquisition time and the total amount of fracturing fluid are not much different, Fig. 9 The morphological differences between (a) and 9(b) are minor; Fig. 9 (a) and Fig. 9 (c) is the relative amplitude anomaly diagram of two adjacent acquisition times under the regular monitoring network in a certain year. Different colors are used to represent different relative amplitude anomaly intervals in the relative amplitude anomaly diagram. Because the acquisition interval is long, the total amount of fracturing fluid increases. Fig. 9 The morphology of (a) and 9(c) is quite different. Fig.10 As shown, Fig.10 (a) and (b) are the relative amplitude anomaly diagrams of two adjacent acquisition times under the continuous acquisition mode of the ring network in a certain year. Different colors are used to represent different relative amplitude anomaly intervals in the relative amplitude anomaly diagram. Because the acquisition time and the total amount of fracturing fluid are not much different, Fig.10 The morphological differences between (a) and 10(b) are small; Fig.10 (c) is the relative amplitude anomaly diagram of two adjacent acquisition times under the annual interval acquisition mode of the ring network. Different colors are used to represent different relative amplitude anomaly intervals in the relative amplitude anomaly diagram. Because the acquisition interval is long, the total amount of fracturing fluid increases, so Fig.10 The morphologies of (a) and 10(c) are quite different.

[0088] As a possible implementation, after the above step (31), the above method for identifying the spatial morphology of hot dry rock fracturing transformation may also include the following operation mode: inverting the amplitude data of different frequencies of the test area before and after the injection of fracturing fluid to obtain the inverted resistivity data of the test area at different times before and after the injection of fracturing fluid; based on the inverted resistivity data of the test area at different times before and after the injection of fracturing fluid, respectively drawing the inverted resistivity profile of the test area within a specified time period before and after the injection of fracturing fluid, the inverted resistivity slice diagram of the test area at different depths within a specified time period before and after the injection of fracturing fluid, and the total longitudinal conductivity plane diagram of the test area at different times before and after the injection of fracturing fluid.

[0089] For example, see Figures 11 to 13 As shown, Fig.11 (a) is the inversion resistivity profile of the same measuring line before the injection of fracturing fluid in the interval acquisition mode in the area to be measured in a certain year. Fig.11 (b) is the inversion resistivity profile of the same measuring line after injection of fracturing fluid in the interval acquisition mode of the area to be measured in a certain year. Different colors are used to represent different resistivity intervals in the inversion resistivity profile; Fig.12 (a) is the inversion resistivity slice diagram of the tested area at a depth of 3700m before and after the injection of fracturing fluid in a certain year. Fig.12 (b) is the inversion resistivity slice diagram of the tested area at a depth of 3800 m before and after the injection of fracturing fluid in a certain year. Different colors are used to represent different resistivity intervals in the inversion resistivity slice diagram; Fig.13 This is the total longitudinal conductivity plane diagram of the area to be tested in a certain year at a certain moment after the injection of fracturing fluid under the interval acquisition method. Different colors are used to represent different longitudinal conductivity intervals in the total longitudinal conductivity plane diagram.

[0090] Relevant personnel according to Fig.12 It can be seen that the low-resistance area of ​​the granite in the middle of the area where the ground measurement network is located changes in a strip shape, and has a gradient resistivity change characteristic with the surrounding area. It can be inferred that the north-south cracks or joints of the granite body are developed, which will have a certain impact on the distribution of the fracturing fluid. Since the total longitudinal conductivity reflects the thickness of the sedimentary strata and the fluctuation of the top surface of the basement, the greater the total longitudinal conductivity, the thicker the sedimentary strata and the deeper the basement is buried, and vice versa; relevant personnel have Fig.13 It can be seen that the sedimentary strata on the northwest and west sides of the area where the ground measurement network is located are thin and the basement is shallow; the sedimentary strata on the northeast and south sides are thick and the basement is deep. Fig.12 , Fig.13The burial depths of the granite mass and the top interface of the basement in the monitoring area are mostly consistent, indicating that the granite mass in the area where the ground measurement network is located is large in scale, which directly affects the changes in stratum sedimentation. On the whole, the basement structure is affected by the scale (thickness, strike) of the granite mass and fluctuates in a strip-like or bead-like manner, and the thickness of the overlying sedimentary strata also varies with the thickness of the granite.

[0091] As a possible implementation, the above-mentioned step S110 (i.e., determining the spatial morphology of the fracturing transformation of the area to be tested based on the distribution of relative electromagnetic anomaly values) may include the following operation modes: determining the resistivity residual abnormal data of the area to be tested within a specified period before and after the injection of the fracturing fluid based on the inverted resistivity data of the area to be tested at different times before and after the injection of the fracturing fluid; drawing a single-section resistivity residual abnormal map of the area to be tested within a specified period before and after the injection of the fracturing fluid and resistivity residual slice maps of different depths in the area to be tested within the specified period before and after the injection of the fracturing fluid based on the resistivity residual abnormal data of the area to be tested within the specified period before and after the injection of the fracturing fluid; drawing a three-dimensional resistivity residual abnormal map of the area to be tested within the specified period before and after the injection of the fracturing fluid based on the single-section resistivity residual abnormal map of the area to be tested within the specified period before and after the injection of the fracturing fluid and the resistivity residual slice maps of different depths in the area to be tested within the specified period before and after the injection of the fracturing fluid; the three-dimensional resistivity residual abnormal map represents the spatial morphology of the fracturing transformation of the area to be tested within the specified period.

[0092] Specifically, according to the data obtained in step p, the resistivity residual abnormal data of the test area at different times before and after the injection of the fracturing fluid can be calculated using the following formula:

[0093]

[0094] Among them, ρrelative is the resistivity residual anomaly (i.e., relative resistivity anomaly), ρ1 is the inverted resistivity data before the injection of fracturing fluid, and ρi is the inverted resistivity data after the injection of fracturing fluid in the i-th section;

[0095] Using the calculated resistivity residual abnormal data of the test area in the specified time period before and after the injection of fracturing fluid, the single-section resistivity residual abnormal map of the test area in the specified time period before and after the injection of fracturing fluid and the resistivity residual slice maps at different depths of the test area in the specified time period before and after the injection of fracturing fluid are drawn respectively. The negative anomaly (i.e., the relative resistivity anomaly is a negative value) indicates the fracturing fluid filling area, i.e., the location of the hot dry rock fracturing transformation space; relevant personnel can quantitatively analyze the spatial distribution characteristics of the fracturing fluid based on the drawn single-section resistivity residual abnormal map and resistivity residual slice map, and draw a three-dimensional resistivity residual abnormal map of the test area in the specified time period before and after the injection of fracturing fluid, so as to stereoscopically depict the spatial morphology of the hot dry rock fracturing transformation through a three-dimensional visualization map.

[0096] For example, see Figures 14 to 16 As shown, Fig.14 This is a single-profile resistivity residual anomaly map before and after the injection of fracturing fluid in the interval acquisition mode of the area to be tested in a certain year. Different colors are used to represent different resistivity residual intervals in the single-profile resistivity residual anomaly map; Fig.15 The resistivity residual slice diagrams of the tested area in a certain year at the depths of 3550m, 3600m, 3650m, 3700m, 3750m and 3800m before and after the injection of fracturing fluid under the interval acquisition mode are shown. Different colors are used to represent different resistivity residual intervals in the resistivity residual slice diagrams; different colors are used to represent different resistivity intervals in the inversion resistivity profile diagrams; Fig.16 This is a three-dimensional resistivity residual anomaly map before and after the injection of fracturing fluid in the interval monitoring acquisition mode in the test area in a certain year, depicting the spatial morphology of hot dry rock fracturing transformation.

[0097] Relevant personnel according to Fig.14 It can be seen that the minimum negative anomaly value (i.e., the minimum value of the resistivity residual) of the single profile in the area where the ground measurement network is located before and after the injection of the fracturing fluid is -0.086, and the range of negative anomaly values ​​less than -0.05 (i.e., the area with a maximum length of 300m and a maximum thickness of 210m) indicates the underground fracturing fluid filling area of ​​this profile, indicating that the major axis of the underground artificial reservoir fracture cluster in this profile is 300m and the maximum thickness is 210m.

[0098] Relevant personnel according to Fig.15 It can be seen that the fracturing fluid is mainly distributed around the bottom of the well, in the south, north and northeast of the bottom of the well, but the fracturing fluid is mainly concentrated around the bottom of the well and in the south, and the liquid distribution in the north and northeast of the bottom of the well is relatively small; vertically, the fracturing fluid is mainly distributed between the burial depth of -3550m and the burial depth of -3800m. Fig.16 It can be seen that an irregular body is formed with the negative anomaly value of the relative amplitude -0.05 as the boundary, and the shape of the irregular body is used to characterize the shape of the hot dry rock fracturing transformation space.

[0099] Based on the above-mentioned hot dry rock hydraulic fracturing transformation spatial morphology recognition method, the embodiment of the present invention also provides another hot dry rock hydraulic fracturing transformation spatial morphology recognition method, see Fig.17 As shown, the method comprises the following steps:

[0100] Step S1701, collect the fracturing section location information, well logging geological layering information, electrical well logging data, and fracturing fluid resistivity parameters of the hot dry rock well. In addition, if there is geophysical exploration results and geological information near the well logging, it is advisable to collect and organize them at the same time.

[0101] Step S1702, based on the thickness of each geological layer and the measured resistivity value of each layer in the well logging geological stratification data, the measured vertical conductivity data of each section of the well logging is calculated.

[0102] Step S1703, based on the thickness of each geological layer and the average rock lithology resistivity of each layer in the well logging geological stratification data, an initial model is established, and the vertical conductivity data of each layer in the initial model is calculated.

[0103] Step S1704, respectively draw a first total longitudinal conductivity curve of the real formation and a second total longitudinal conductivity curve of the model formation, and adjust the size of the mean value of the rock lithology resistivity until the deviation between the second total longitudinal conductivity curve and the first total longitudinal conductivity curve is within a preset range, thereby obtaining a geological resistivity model.

[0104] Step S1705: Establish a fracture model of the area to be tested based on the geological resistivity model and the preliminary judgment information obtained in advance.

[0105] Step S1706: Based on the above fracture model, a forward numerical simulation of the area to be tested is carried out, and a corresponding forward simulation diagram is drawn.

[0106] Step S1707, determining electromagnetic parameters of the area to be measured in combination with the forward modeling diagram, the total amount of injected fracturing fluid and the plane distribution range of microseismic events.

[0107] Step S1708, an excitation source is arranged in the area to be tested, so as to continuously emit pulse excitation current to the ground through the excitation source and generate induced eddy current underground.

[0108] Step S1709, before injecting fracturing fluid into the area to be tested, a ground measuring network is laid out in the area to be tested with the ground projection of the bottom of the hot dry rock fracturing well in the area to be tested as the center.

[0109] Step S1710, before and after the fracturing fluid is injected into the area to be tested, the data acquisition station is used to collect the horizontal induced electric field component data generated by the changes in the above-mentioned induced eddy current in the area where the ground measuring network is located, and the background field original data and the abnormal field original data of the area to be tested are obtained.

[0110] Step S1711, after checking that the electromagnetic method parameters are correct, the background field raw data and the abnormal field raw data are filtered, superimposed and Fourier transformed in turn to obtain the real, imaginary components and coordinate data of different frequencies of all measuring points, and the real, imaginary components and coordinate data of the emission current.

[0111] Step S1712, a database is established for the data obtained after Fourier transformation, and current normalization processing is performed to obtain amplitude and phase data of different frequencies in the test area before and after the injection of fracturing fluid.

[0112] Step S1713, using the amplitude and phase data of different frequencies in the test area before and after the injection of the fracturing fluid, select a frequency suitable for the target burial depth, and calculate the relative amplitude abnormal data of the test area in different time periods before and after the injection of the fracturing fluid.

[0113] Step S1714, using the calculated relative amplitude anomaly data of the test area in different time periods before and after the injection of the fracturing fluid, draw a relative amplitude anomaly distribution diagram of the test area at different times before and after the injection of the fracturing fluid.

[0114] Step S1715, inverting the amplitude data of different frequencies in the test area before and after the injection of the fracturing fluid, and obtaining the inverted resistivity data of the test area at different times before and after the injection of the fracturing fluid, line by line and point by point.

[0115] Step S1716, based on the inversion resistivity data of the test area at different times before and after the injection of the fracturing fluid, draw the inversion resistivity profile of the test area within a specified period before and after the injection of the fracturing fluid, the inversion resistivity slice diagram of the test area at different depths within the specified period before and after the injection of the fracturing fluid, and the total longitudinal conductivity plane diagram of the test area at different times before and after the injection of the fracturing fluid.

[0116] Relevant personnel can combine the maps obtained in this step with logging and geological information to analyze the formation structure and fracture transformation in the area to be tested, achieve a comprehensive evaluation of reservoir transformation and fracture connectivity, and provide suggestions for wellbore deviation or directional well target points.

[0117] Step S1717, using the inverted resistivity data of the test area at different times before and after the injection of the fracturing fluid, calculate the resistivity residual abnormal data of the test area in a specified period before and after the injection of the fracturing fluid.

[0118] Step S1718, using the resistivity residual abnormal data of the test area within the specified time period before and after the injection of fracturing fluid, draw a single-section resistivity residual abnormal map of the test area within the specified time period before and after the injection of fracturing fluid and a resistivity residual slice map of different depths of the test area within the specified time period before and after the injection of fracturing fluid.

[0119] Step S1719, based on the single-section resistivity residual abnormal map of the test area within the specified time period before and after the injection of fracturing fluid and the resistivity residual slice map of different depths in the test area within the specified time period before and after the injection of fracturing fluid, draw a three-dimensional resistivity residual abnormal map of the test area within the specified time period before and after the injection of fracturing fluid.

[0120] Based on the above-mentioned hot dry rock fracturing transformation space morphology recognition method, the embodiment of the present invention also provides a hot dry rock fracturing transformation space morphology recognition system, see Fig.18 As shown, the system includes:

[0121] The first determination module 1802 is used to determine the electromagnetic parameters of the area to be measured based on the forward simulation results obtained by performing forward numerical simulation on the area to be measured; wherein the electromagnetic parameters include: point spacing, electrode spacing, transmitting and receiving spacing, supply electrode spacing, supply current, excitation waveform, excitation frequency and number of single-frequency excitation cycles.

[0122] The first acquisition module 1804 is used to acquire the original data of the area to be tested before the fracturing fluid is injected based on the ground measurement network deployed in the area to be tested, so as to obtain the background field original data; wherein the original data includes: the excitation frequency of each measuring point in the ground measurement network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point.

[0123] The second acquisition module 1806 is used to acquire the original data of the area to be tested after the fracturing fluid is injected based on the ground measurement network deployed in the area to be tested, so as to obtain the original data of the abnormal field.

[0124] A second determination module 1808 is used to determine the relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid based on the background field original data and the abnormal field original data;

[0125] The third determination module 1810 is used to determine the fracturing reconstruction spatial form of the area to be tested based on the relative electromagnetic anomaly value distribution.

[0126] The embodiment of the present invention provides a hot dry rock fracturing transformation spatial morphology identification system, which determines electromagnetic method parameters by forward numerical simulation, obtains background field original data before fracturing transformation and abnormal field original data after fracturing transformation by laying out ground measurement network, determines relative electromagnetic abnormal value distribution before and after fracturing transformation based on background field original data and abnormal field original data, and determines fracturing transformation spatial morphology based on relative electromagnetic abnormal value distribution. The above technology can alleviate the technical problems of weak anti-interference ability, limited detection depth, insufficient detection accuracy, and poor construction flexibility existing in the prior art.

[0127] The above-mentioned first determination module 1802 is also used to: establish a geological resistivity model of the area to be tested based on the well logging geological stratification data, well logging segmentation data and well logging resistivity data of each section of the area to be tested; based on the geological resistivity model, use the electromagnetic method to perform forward numerical simulation of the area to be tested to obtain forward simulation results; wherein the forward simulation results include simulated electromagnetic data of the area to be tested before the injection of fracturing fluid, and simulated electromagnetic data of the area to be tested after the injection of fracturing fluid; determine the electromagnetic method parameters based on the forward simulation results.

[0128] The first determination module 1802 is also used to: calculate the measured vertical conductivity data of each section of the well logging based on the thickness of each geological layer and the measured resistivity value of each layer in the well logging geological stratification data; establish an initial model based on the thickness of each geological layer and the average rock lithology resistivity of each layer in the well logging geological stratification data, and calculate the vertical conductivity data of each layer in the initial model; draw a first total vertical conductivity curve of the real formation and a second total vertical conductivity curve of the model formation respectively, and adjust the size of the average rock lithology resistivity until the deviation between the second total vertical conductivity curve and the first total vertical conductivity curve is within a preset range, so as to obtain the geological resistivity model.

[0129] The first determination module 1802 is also used to: establish a fracture model of the area to be tested based on the geological resistivity model and the preliminary judgment information obtained in advance; wherein the preliminary judgment information includes: fracture scale, fracture angle, fracture morphology, fracture burial depth, fracture water richness and fracturing fluid resistivity; based on the fracture model, use electromagnetic method to perform forward numerical simulation on the area to be tested to obtain the forward simulation result.

[0130] The relative electromagnetic anomaly value distribution of the above-mentioned test area before and after the injection of fracturing fluid includes the relative amplitude anomaly distribution of the test area in different time periods before and after the injection of fracturing fluid; based on this, the above-mentioned second determination module 1808 is also used to: pre-process the background field original data and the abnormal field original data to obtain the amplitude data of different frequencies of the test area before and after the injection of fracturing fluid; wherein the preprocessing includes at least one of the following: filtering, superposition, Fourier transform and current normalization; based on the amplitude data of the specified frequency of the test area before and after the injection of fracturing fluid, determine the relative amplitude anomaly distribution of the test area in different time periods before and after the injection of fracturing fluid.

[0131] Based on the above Fig.18 The hot dry rock fracturing transformation space morphology recognition system shown in the embodiment of the present invention also provides another hot dry rock fracturing transformation space morphology recognition system, see Fig.19 As shown, the system also includes:

[0132] The inversion module 1812 is used to invert the amplitude data of different frequencies of the test area before and after the injection of the fracturing fluid, and obtain the inversion resistivity data of the test area at different times before and after the injection of the fracturing fluid; based on the inversion resistivity data of the test area at different times before and after the injection of the fracturing fluid, draw the inversion resistivity profile of the test area within a specified period before and after the injection of the fracturing fluid, the inversion resistivity slice diagram of different depths of the test area within a specified period before and after the injection of the fracturing fluid, and the total longitudinal conductivity plane diagram of the test area at different times before and after the injection of the fracturing fluid.

[0133] Based on this, the third determination module 1810 is also used to: determine the resistivity residual abnormal data of the test area within a specified time period before and after the injection of the fracturing fluid based on the inverted resistivity data of the test area at different times before and after the injection of the fracturing fluid; draw a single-section resistivity residual abnormal map of the test area within a specified time period before and after the injection of the fracturing fluid and a resistivity residual slice map of different depths in the test area within a specified time period before and after the injection of the fracturing fluid based on the resistivity residual abnormal data of the test area within a specified time period before and after the injection of the fracturing fluid; draw a three-dimensional resistivity residual abnormal map of the test area within a specified time period before and after the injection of the fracturing fluid based on the single-section resistivity residual abnormal map of the test area within a specified time period before and after the injection of the fracturing fluid and the resistivity residual slice map of different depths in the test area within the specified time period before and after the injection of the fracturing fluid; the three-dimensional resistivity residual abnormal map represents the spatial morphology of the fracturing transformation of the test area within the specified time period.

[0134] The implementation principle and technical effects of the hot dry rock fracturing transformation spatial morphology identification system provided in the embodiment of the present invention are the same as those of the aforementioned hot dry rock fracturing transformation spatial morphology identification method embodiment. For the sake of brief description, for matters not mentioned in the system embodiment, reference can be made to the corresponding contents in the aforementioned method embodiment.

[0135] An embodiment of the present invention provides an electronic device. Specifically, the electronic device includes a processor and a storage system. A computer program is stored on the storage system. When the computer program is run by the processor, the method for identifying the spatial morphology of hot dry rock fracturing transformation described in any one of the above-mentioned embodiments is executed.

[0136] Fig. 20 A structural diagram of an electronic device provided in an embodiment of the present invention, the electronic device 100 includes: a processor 200, a memory 201, a bus 202 and a communication interface 203, wherein the processor 200, the communication interface 203 and the memory 201 are connected via the bus 202; the processor 200 is used to execute an executable module stored in the memory 201, such as a computer program.

[0137] The memory 201 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 203 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0138] The bus 202 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 20 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0139] Among them, the memory 201 is used to store programs, and the processor 200 executes the program after receiving the execution instruction. The method executed by the system for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 200 or implemented by the processor 200.

[0140] The processor 200 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 200. The above processor 200 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method for identifying the spatial morphology of hot dry rock fracturing transformation disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor, or a combination of hardware and software modules in the decoding processor. The software module can be located in a random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, register or other mature storage media in the art. The storage medium is located in the memory 201, and the processor 200 reads the information in the memory 201, and completes the steps of the above-mentioned hot dry rock fracturing transformation spatial morphology recognition method in combination with its hardware.

[0141] An embodiment of the present invention further provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the method for identifying the spatial morphology of hot dry rock fracturing transformation described in the previous method embodiment. The specific implementation can be found in the previous method embodiment and will not be repeated here.

[0142] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for identifying the spatial morphology of hot dry rock fracturing, characterized in that: include: Based on the well logging geological stratification data, well logging segmentation data and well logging resistivity data of each segment of the area to be tested, a geological resistivity model of the area to be tested is established; Based on the geological resistivity model, the electromagnetic method is used to perform forward numerical simulation on the area to be tested to obtain forward simulation results; wherein the forward simulation results include simulated electromagnetic data of the area to be tested before the injection of fracturing fluid and simulated electromagnetic data of the area to be tested after the injection of fracturing fluid; Determine the electromagnetic parameters of the area to be measured based on the forward simulation results; wherein the electromagnetic parameters include point spacing, electrode spacing, transmitting and receiving spacing, supply electrode spacing, supply current, excitation waveform, excitation frequency and single frequency excitation cycle number; Based on the ground measuring network arranged in the area to be measured, the original data of the area to be measured before the fracturing fluid is injected is obtained to obtain the background field original data; wherein the original data includes: the excitation frequency of each measuring point in the ground measuring network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point; Based on the ground measuring network arranged in the area to be measured, the original data of the area to be measured after the fracturing fluid is injected is obtained to obtain the original data of the abnormal field; Based on the background field original data and the abnormal field original data, determining the relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid; Determining the spatial morphology of the hydraulic fracturing transformation in the area to be tested based on the relative electromagnetic anomaly value distribution; The step of establishing a geological resistivity model of the area to be measured based on the well logging geological stratification data, well logging segmentation data and well logging resistivity data of each segment of the area to be measured comprises: calculating the measured vertical conductivity data of each segment of the well logging based on the thickness of each geologically divided layer and the measured resistivity value of each layer in the well logging geological stratification data; establishing an initial model based on the thickness of each geologically divided layer and the mean value of the rock lithology resistivity of each layer in the well logging geological stratification data, and calculating the vertical conductivity data of each layer in the initial model; respectively drawing a first total vertical conductivity curve of the real formation and a second total vertical conductivity curve of the model formation, and adjusting the size of the mean value of the rock lithology resistivity until the deviation between the second total vertical conductivity curve and the first total vertical conductivity curve is within a preset range, thereby obtaining the geological resistivity model.

2. The method according to claim 1, characterized in that: The relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid includes the relative amplitude abnormal distribution of the test area in different time periods before and after the injection of the fracturing fluid; The step of determining the relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid based on the background field original data and the abnormal field original data comprises: Preprocessing the background field raw data and the abnormal field raw data to obtain amplitude data of different frequencies of the test area before and after the injection of fracturing fluid; wherein the preprocessing includes at least one of the following: filtering, superposition, Fourier transform and current normalization; Based on the amplitude data of the specified frequency before and after the injection of the fracturing fluid in the test area, the relative amplitude abnormal distribution in different time periods before and after the injection of the fracturing fluid in the test area is determined.

3. The method according to claim 2, characterized in that After the step of preprocessing the background field raw data and the abnormal field raw data to obtain the amplitude data of different frequencies before and after the injection of the fracturing fluid in the test area, the method further comprises: Inverting the amplitude data of different frequencies in the test area before and after the injection of the fracturing fluid to obtain the inverted resistivity data of the test area at different times before and after the injection of the fracturing fluid; Based on the inversion resistivity data of the test area at different times before and after the injection of fracturing fluid, the inversion resistivity profile of the test area within a specified period before and after the injection of fracturing fluid, the inversion resistivity slice diagram of the test area at different depths within a specified period before and after the injection of fracturing fluid, and the total longitudinal conductivity plane diagram of the test area at different times before and after the injection of fracturing fluid are respectively drawn.

4. The method according to claim 1, characterized in that: Based on the geological resistivity model, the forward numerical simulation of the area to be measured is performed by electromagnetic method to obtain the forward simulation result, including: Based on the geological resistivity model and the preliminary judgment information obtained in advance, a fracture model of the area to be tested is established; wherein the preliminary judgment information includes: fracture scale, fracture angle, fracture morphology, fracture burial depth, fracture water richness and fracturing fluid resistivity; Based on the crack model, the electromagnetic method is used to perform forward numerical simulation on the area to be tested to obtain the forward simulation result.

5. The method according to claim 3, characterized in that: The step of determining the spatial morphology of the hydraulic fracturing transformation in the area to be tested based on the relative electromagnetic anomaly value distribution includes: Determine resistivity residual abnormal data of the test area in a specified period before and after the injection of the fracturing fluid based on the inverted resistivity data of the test area at different times before and after the injection of the fracturing fluid; Based on the resistivity residual abnormal data of the test area within a specified period before and after the injection of the fracturing fluid, a single-section resistivity residual abnormal map of the test area within a specified period before and after the injection of the fracturing fluid and resistivity residual slice maps of different depths of the test area within a specified period before and after the injection of the fracturing fluid are respectively drawn; Based on the single-section resistivity residual abnormal map of the test area within the specified time period before and after the injection of fracturing fluid and the resistivity residual slice maps at different depths of the test area within the specified time period before and after the injection of fracturing fluid, a three-dimensional resistivity residual abnormal map of the test area within the specified time period before and after the injection of fracturing fluid is drawn; the three-dimensional resistivity residual abnormal map characterizes the spatial morphology of the fracturing transformation of the test area within the specified time period.

6. A hot dry rock fracturing transformation space morphology recognition system, characterized in that: include: The first determination module is used to: establish a geological resistivity model of the area to be tested based on the logging geological stratification data, logging segmentation data and logging resistivity data of each segment of the area to be tested; based on the geological resistivity model, use the electromagnetic method to perform forward numerical simulation on the area to be tested to obtain forward simulation results; wherein the forward simulation results include simulated electromagnetic data of the area to be tested before the injection of fracturing fluid and simulated electromagnetic data of the area to be tested after the injection of fracturing fluid; determine the electromagnetic method parameters of the area to be tested based on the forward simulation results; wherein the electromagnetic method parameters include: point spacing, electrode spacing, transceiver spacing, supply electrode spacing, power supply current, excitation waveform, excitation frequency and single frequency excitation cycle number; The first acquisition module is used to acquire the original data of the area to be tested before the fracturing fluid is injected based on the ground measurement network deployed in the area to be tested, so as to obtain the original data of the background field; wherein the original data includes: the excitation frequency of each measuring point in the ground measurement network, the emission current of each measuring point, the receiving data of each measuring point and the coordinates of each measuring point; A second acquisition module is used to acquire the original data of the area to be tested after the fracturing fluid is injected based on the ground measurement network deployed in the area to be tested, so as to obtain the original data of the abnormal field; A second determination module is used to determine the relative electromagnetic abnormal value distribution of the test area before and after the injection of the fracturing fluid based on the background field original data and the abnormal field original data; A third determination module is used to determine the fracturing reconstruction spatial form of the area to be tested based on the relative electromagnetic anomaly value distribution; The first determination module is also used to: calculate the measured vertical conductivity data of each section of the well logging based on the thickness of each geological layer and the measured resistivity value of each layer in the well logging geological stratification data; establish an initial model based on the thickness of each geological layer and the average rock lithology resistivity of each layer in the well logging geological stratification data, and calculate the vertical conductivity data of each layer in the initial model; draw a first total longitudinal conductivity curve of the real formation and a second total longitudinal conductivity curve of the model formation respectively, and adjust the size of the average rock lithology resistivity until the deviation between the second total longitudinal conductivity curve and the first total longitudinal conductivity curve is within a preset range, so as to obtain the geological resistivity model.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable medium having a non-volatile program code executable by a processor, characterized in that: The program code enables the processor to execute the method according to any one of claims 1 to 5.

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