Reservoir ground stress prediction method and device, electronic equipment and storage medium

Abstract

The invention discloses a reservoir ground stress prediction method and device, electronic equipment and a storage medium. The method comprises the steps that first logging information and actual drilling multi-source data of a pilot well are obtained, and first target key parameters of the pilot well are determined based on the first logging information and the actual drilling multi-source data; determining a key parameter mapping relationship between the horizontal well and the pilot well; determining a second target key parameter of the horizontal well based on the key parameter mapping relation and the first target key parameter; and according to the second target key parameter and second logging information of the horizontal well, determining the reservoir horizontal ground stress of the horizontal well. According to the scheme, the reservoir horizontal crustal stress of the horizontal well can be reasonably predicted based on the logging information of the pilot well and the actual drilling multi-source data, so that the geomechanical characteristics of the shale reservoir in southern Sichuan can be fully known and finely described, guidance is provided for well drilling of the horizontal well and optimization design of hydraulic fracturing parameters, and the shale gas yield is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of unconventional shale oil and gas drilling and reservoir production enhancement and transformation, and in particular to a reservoir geostress prediction method, device, electronic equipment and storage medium. Background Art

[0002] Shale gas resources have great potential, but the horizontal stress differences of shale gas reservoirs in southern Sichuan are large, resulting in unsatisfactory fracturing effects of shale gas wells. As we all know, geostress is an important basis for various engineering decisions in the development of shale gas reservoirs, supporting the smooth implementation of well selection, drilling, pressure and management, which is conducive to the full utilization and efficient development of shale gas reservoirs. In terms of well selection, it mainly supports the optimization of engineering sweet spots and the optimization of horizontal well positions. In terms of pressure wells, it mainly supports the optimization of completion design, morphological simulation of fracturing cracks, proppant optimization, and optimization of fracturing parameters. In terms of well management, it mainly supports the optimization of repeated fracturing gas wells, analysis of the impact of inter-well pressure channeling, optimization of production systems, and development of three-dimensional well networks. Since geostress characteristics are the basis of the reservoir properties of shale gas reservoirs and the core of geological selection and evaluation technology, geostress characteristic evaluation technology is a key technology for shale gas exploration and development and an indispensable key link. However, due to the influence of multiple tectonic movements, the shale reservoirs in southern Sichuan have large differences in burial depth and the development of natural fractures and faults, which makes geomechanical modeling and analysis difficult, especially the in-situ stress is difficult to obtain accurately. Therefore, the accuracy and reliability of in-situ stress are of great significance to the efficient development of shale gas resources.

[0003] As we all know, horizontal wells have become the key foundation for the efficient development of shale gas. However, due to factors such as logging technology, wellbore trajectory and complex formation structure, it is difficult for some horizontal wells to obtain all the data required for geostress modeling. For this reason, pilot wells and horizontal wells have become the preferred well types for shale gas evaluation wells, which are helpful to understand the lithology, physical properties, electrical properties, oil content, oil-water relationship, structural conditions and changes of the target layer, so as to determine the target parameters such as A and B of the horizontal well. At the same time, the pilot well can relatively easily obtain the complete data required for geostress modeling, and can also obtain relatively complete experimental data through downhole coring as the correction data of the geostress profile. However, the geostress state of the pilot well is difficult to be directly converted into the geostress state of the horizontal well, and the DFIT data used to correct the geostress profile only comes from the test of the first fracturing stage of the horizontal well. In addition, the horizontal well cannot realize downhole coring on a large scale, which makes it difficult to provide effective data support for the correction of the geostress profile. These make its horizontal geostress profile usually rely on the data of adjacent wells, and it is difficult to provide an effective reference for the fracturing design of the entire horizontal section. Summary of the invention

[0004] The present invention provides a reservoir geostress prediction method, device, electronic equipment and storage medium, which can reasonably predict the reservoir horizontal geostress of a horizontal well based on the logging data of a pilot well and actual drilling multi-source data.

[0005] According to one aspect of the present invention, a reservoir in-situ stress prediction method is provided, comprising:

[0006] Acquire first well logging data and actual drilling multi-source data of the pilot well, and determine first target key parameters of the pilot well based on the first well logging data and the actual drilling multi-source data;

[0007] Determine a key parameter mapping relationship between the horizontal well and the pilot well;

[0008] Determining a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter;

[0009] The horizontal geostress of the reservoir of the horizontal well is determined according to the second target key parameter and the second logging data of the horizontal well.

[0010] According to another aspect of the present invention, there is provided a reservoir in-situ stress prediction device, comprising:

[0011] A first target key parameter determination module, used to obtain first well logging data and actual drilling multi-source data of the pilot well, and determine the first target key parameter of the pilot well based on the first well logging data and the actual drilling multi-source data;

[0012] A key parameter mapping relationship determination module, used to determine the key parameter mapping relationship between the horizontal well and the pilot well;

[0013] A second target key parameter determination module, used to determine a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter;

[0014] The reservoir horizontal geostress determination module is used to determine the reservoir horizontal geostress of the horizontal well according to the second target key parameter and the second logging data of the horizontal well.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the reservoir in-situ stress prediction method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the reservoir in-situ stress prediction method described in any embodiment of the present invention when executed by a processor.

[0020] The reservoir geostress prediction scheme of the embodiment of the present invention obtains the first logging data and actual drilling multi-source data of the pilot well, and determines the first target key parameter of the pilot well based on the first logging data and the actual drilling multi-source data; determines the key parameter mapping relationship between the horizontal well and the pilot well; determines the second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter; determines the horizontal geostress of the reservoir of the horizontal well according to the second target key parameter and the second logging data of the horizontal well. The technical scheme provided by the embodiment of the present invention can reasonably predict the horizontal geostress of the reservoir of the horizontal well based on the logging data and actual drilling multi-source data of the pilot well, thereby helping to fully understand and finely describe the geomechanical characteristics of the shale reservoir in southern Sichuan, provide guidance for the optimization design of horizontal well drilling and hydraulic fracturing parameters, and increase shale gas production, which is of great significance to the development of deep shale gas resources in the Sichuan Basin.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flow chart of a reservoir geostress prediction method provided in Example 1 of the present invention;

[0024] Figure 2 A flow chart of a reservoir geostress prediction method provided in Embodiment 2 of the present invention;

[0025] Figure 3A cross-sectional schematic diagram of a theoretical value of a rock mechanics parameter, a theoretical value of an overburden formation pressure, and a theoretical value of a formation pore pressure respectively determined according to well logging data of a pilot well provided in an embodiment of the present invention;

[0026] Figure 4 A cross-sectional schematic diagram of theoretical values ​​of horizontal geostress in a pilot well provided by an embodiment of the present invention;

[0027] Figure 5 A projection diagram of core experimental test data of a pilot well and theoretical values ​​of rock mechanics parameters provided by an embodiment of the present invention;

[0028] Figure 6 A projection diagram of multi-source data of actual drilling of a pilot well and a formation pore pressure profile value provided by an embodiment of the present invention;

[0029] Figure 7 A projection diagram of multi-source data of actual drilling of a pilot well and theoretical values ​​of horizontal geostress profile provided by an embodiment of the present invention;

[0030] Figure 8 An actual value diagram of the horizontal geostress profile of a pilot well calibrated based on actual drilling multi-source data provided by an embodiment of the present invention;

[0031] Fig. 9 A reservoir horizontal geostress profile diagram of a horizontal well based on the geostress data mapping of a pilot well provided in an embodiment of the present invention;

[0032] Fig.10 A schematic diagram of the structure of a reservoir geostress prediction device provided in Embodiment 3 of the present invention;

[0033] Fig.11 It is a schematic diagram of the structure of an electronic device for implementing the reservoir in-situ stress prediction method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] Embodiment 1

[0037] Figure 1 This is a flow chart of a reservoir geostress prediction method provided in Example 1 of the present invention. This embodiment is applicable to the case of predicting reservoir geostress in horizontal wells. The method can be executed by a reservoir geostress prediction device. The reservoir geostress prediction device can be implemented in the form of hardware and / or software. The reservoir geostress prediction device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0038] S110, acquiring first well logging data and actual drilling multi-source data of the pilot well, and determining first target key parameters of the pilot well based on the first well logging data and the actual drilling multi-source data.

[0039] In an embodiment of the present invention, the logging data of the pilot well is obtained. For the convenience of description, the logging data of the pilot well is referred to as the first logging data. The logging data of the pilot well (i.e., the first logging data) may include natural gamma, density, acoustic wave and other logging data. The actual drilling multi-source data of the pilot well is obtained, wherein the actual drilling multi-source data may be multi-source data such as drilling-logging-testing of the pilot well. The first target key parameters of the pilot well are determined according to the logging data and the actual drilling multi-source data of the pilot well. The first target key parameters may be understood as the values ​​of the key parameters in the corresponding calculation model in the process of determining the actual values ​​of the rock mechanics parameters, the actual values ​​of the formation pore pressure and the actual values ​​of the horizontal ground stress of the pilot well. Exemplarily, the first target key parameters may include target rock mechanics parameters, target formation pore pressure parameters and target structural stress coefficients. Among them, the target rock mechanics parameters are the rock mechanics parameters in the rock mechanics parameter conversion model of the pilot well when the actual values ​​of the rock mechanics parameters of the pilot well are determined based on the rock mechanics parameter conversion model of the pilot well; the target formation pore pressure parameters are the formation pore pressure parameters in the formation pore pressure model of the pilot well when the actual values ​​of the formation pore pressure of the pilot well are determined based on the formation pore pressure model of the pilot well; the target tectonic stress coefficient is the tectonic stress coefficient in the geostress model of the pilot well when the actual values ​​of the horizontal geostress of the pilot well are determined based on the geostress model of the pilot well.

[0040] S120, determining a key parameter mapping relationship between the horizontal well and the pilot well.

[0041] In an embodiment of the present invention, a key parameter mapping relationship between a horizontal well and a pilot well is obtained, wherein the key parameter mapping relationship is used to characterize the corresponding relationship between the key parameters of the horizontal well and the key parameters of the pilot well. Optionally, determining the key parameter mapping relationship between the horizontal well and the pilot well includes: under the premise of controlling the stratum of the pilot well to match the stratum of the horizontal well, determining the key parameter mapping relationship between the horizontal well and the pilot well in the process of performing logging stretching from the pilot well to the horizontal well based on the vertical depth offset between the vertical depth of the pilot well and the vertical depth of the horizontal well. Exemplarily, the stratum of the pilot well is matched with the stratum of the horizontal well, and the logging stretching based on the vertical depth mark and the pilot well to the horizontal well is performed in combination with the vertical depth offset (i.e., the vertical depth difference) between the vertical depth of the pilot well and the vertical depth of the horizontal well, thereby completing the establishment of the physical mapping relationship of the key parameters involved in the pilot well and the horizontal well.

[0042] Exemplarily, the first target key parameters include target rock mechanics parameters, target formation pore pressure parameters and target tectonic stress coefficient, then the key parameter mapping relationship between the horizontal well and the pilot well may include the rock mechanics parameter mapping relationship between the horizontal well and the pilot well, the formation pore pressure parameter mapping relationship between the horizontal well and the pilot well, and the tectonic stress coefficient mapping relationship between the horizontal well and the pilot well.

[0043] S130. Determine a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter.

[0044] In an embodiment of the present invention, according to the key parameter mapping relationship between the horizontal well and the pilot well, the first target key parameter of the pilot well is converted into the target key parameter of the horizontal well. For the convenience of description, the target key parameter of the horizontal well is referred to as the second target key parameter. Exemplarily, according to the rock mechanics parameter mapping relationship between the horizontal well and the pilot well, the target rock mechanics parameters of the pilot well are converted into the target rock mechanics parameters of the horizontal well; according to the formation pore pressure parameter mapping relationship between the horizontal well and the pilot well, the target formation pore pressure parameters of the pilot well are converted into the target formation pore pressure parameters of the horizontal well; according to the tectonic stress coefficient mapping relationship between the horizontal well and the pilot well, the target tectonic stress coefficient of the pilot well is converted into the target tectonic stress coefficient of the horizontal well.

[0045] S140. Determine the reservoir horizontal geostress of the horizontal well according to the second target key parameter and the second logging data of the horizontal well.

[0046] In an embodiment of the present invention, the logging data of the horizontal well is obtained. For the convenience of description, the logging data of the horizontal well is referred to as the second logging data. According to the second target key parameter (i.e., the target key parameter of the horizontal well) and the second logging data of the horizontal well, the horizontal geostress of the reservoir of the horizontal well is determined. Exemplarily, the actual values ​​of the rock mechanics parameters of the horizontal well are calculated according to the target rock mechanics parameters of the horizontal well and the logging data of the horizontal well (i.e., the second logging data), the actual value of the formation pore pressure of the horizontal well is calculated according to the target formation pore pressure parameters of the horizontal well and the logging data of the horizontal well (i.e., the second logging data), and the horizontal geostress of the reservoir of the horizontal well is calculated according to the actual values ​​of the rock mechanics parameters of the horizontal well, the actual value of the formation pore pressure of the horizontal well and the target structural stress coefficient of the horizontal well.

[0047] The reservoir geostress prediction method of the embodiment of the present invention obtains the first logging data and actual drilling multi-source data of the pilot well, and determines the first target key parameter of the pilot well based on the first logging data and the actual drilling multi-source data; determines the key parameter mapping relationship between the horizontal well and the pilot well; determines the second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter; determines the horizontal geostress of the reservoir of the horizontal well according to the second target key parameter and the second logging data of the horizontal well. The technical solution provided by the embodiment of the present invention can reasonably predict the horizontal geostress of the reservoir of the horizontal well based on the logging data and actual drilling multi-source data of the pilot well, thereby helping to fully understand and finely describe the geomechanical characteristics of the shale reservoir in southern Sichuan, provide guidance for the optimization design of horizontal well drilling and hydraulic fracturing parameters, and increase shale gas production, which is of great significance to the development of deep shale gas resources in the Sichuan Basin.

[0048] Embodiment 2

[0049] Figure 2 A flow chart of a reservoir geostress prediction method provided in the second embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:

[0050] S210, obtaining first logging data of the pilot well and actual drilling multi-source data; wherein the actual drilling multi-source data includes drilling-logging data, formation pressure test data and core experiment test data.

[0051] S220. Calculate theoretical values ​​of rock mechanics parameters, theoretical values ​​of overburden pressure, and theoretical values ​​of formation pore pressure of the pilot well based on the first well logging data.

[0052] Optionally, the first logging data includes natural gamma logging data, density logging data and sonic logging data; calculating the theoretical values ​​of rock mechanical parameters, theoretical values ​​of overburden pressure and theoretical values ​​of formation pore pressure of the pilot well based on the first logging data includes: calculating the theoretical values ​​of rock mechanical parameters of the pilot well based on the natural gamma logging data and the sonic logging data; calculating the theoretical values ​​of overburden pressure of the pilot well based on the density logging data; calculating the theoretical values ​​of formation pore pressure of the pilot well based on the sonic logging data. Optionally, calculating the theoretical values ​​of rock mechanical parameters of the pilot well based on the natural gamma logging data and the sonic logging data includes: determining the lithology type of the pilot well based on the natural gamma logging data; wherein the lithology type includes mudstone and non-mudstone; determining a rock mechanical parameter conversion model according to the lithology type, and calculating the theoretical values ​​of rock mechanical parameters of the pilot well based on the natural gamma logging data, the sonic logging data and the rock mechanical parameter model.

[0053] In the embodiment of the present invention, based on the natural gamma logging data of the pilot well, the lithology type of the pilot well is divided into shale and non-shale lithology profiles. Different rock mechanics parameter conversion models are selected for different lithologies, and the theoretical values ​​of rock mechanics parameter profiles such as elastic modulus, Poisson's ratio, uniaxial compressive strength and internal friction angle are determined based on the natural gamma logging data, sonic logging data and rock mechanics parameter model. Among them:

[0054] Dynamic elastic modulus of rock E d It can be expressed as:

[0055]

[0056] Dynamic Poisson's ratio of rock μ d It can be expressed as:

[0057]

[0058] Dynamic elastic modulus of rock E s It can be expressed as:

[0059] E s =A Ed-s ×E d +B Ed-s (3)

[0060] Static Poisson's ratio of rock μ s It can be expressed as:

[0061]

[0062] The uniaxial compressive strength (UCS) can be expressed as:

[0063]

[0064] The internal friction angle φ can be expressed as:

[0065]

[0066] In the embodiment of the present invention, based on the pilot well density logging data, the theoretical value of the overburden pressure is calculated using the density integration method, wherein the theoretical value of the overburden pressure can be expressed as:

[0067]

[0068] Based on the acoustic logging data of the pilot well, the theoretical value of the formation pore pressure is calculated using the Bower method, where the theoretical value of the formation pore pressure can be expressed as:

[0069]

[0070] For example, Figure 3A cross-sectional schematic diagram of a theoretical value of a rock mechanics parameter, a theoretical value of overburden pressure, and a theoretical value of formation pore pressure respectively determined according to well logging data of a pilot well provided in an embodiment of the present invention.

[0071] S230. Determine the theoretical value of horizontal geostress of the pilot well according to the theoretical value of the rock mechanics parameter, the theoretical value of the overburden stratum pressure and the theoretical value of the formation pore pressure.

[0072] In the embodiment of the present invention, the theoretical value of horizontal ground stress of the pilot well is determined by calculation using a combined spring model based on the theoretical values ​​of rock mechanics parameters, the theoretical value of overlying formation pressure and the theoretical value of formation pore pressure. Figure 4 A cross-sectional schematic diagram of a theoretical value of horizontal geostress of a pilot well provided in an embodiment of the present invention. The theoretical value of horizontal geostress of the pilot well can be calculated according to the following formula:

[0073]

[0074] S240. Based on the actual drilling multi-source data, the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure and the theoretical values ​​of the horizontal ground stress are respectively corrected, and the first target key parameters of the pilot well are determined during the correction process.

[0075] In an embodiment of the present invention, the theoretical value of horizontal geostress of the pilot well is corrected according to the multi-source data of drilling, logging, and testing of the pilot well, and the actual value of horizontal geostress of the pilot well is determined, thereby clarifying the key parameters involved in the calculation model of formation pressure and geostress. Similarly, the theoretical value of rock mechanics parameters of the pilot well is corrected according to the multi-source data of drilling, logging, and testing of the pilot well, and the actual value of rock mechanics parameters of the pilot well is determined, thereby clarifying the key parameters involved in the rock mechanics parameter conversion model. The theoretical value of formation pore pressure of the pilot well is corrected according to the multi-source data of drilling, logging, and testing of the pilot well, and the actual value of formation pore pressure of the pilot well is determined, thereby clarifying the key parameters involved in the calculation model in the Bower method.

[0076] Optionally, the actual drilling multi-source data includes drilling-logging data, formation pressure test data and core experimental test data; based on the actual drilling multi-source data, the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure and the theoretical values ​​of the horizontal ground stress are corrected respectively, and the first target key parameters of the pilot well are determined during the correction process, including: placing the core experimental test data and the theoretical values ​​of the rock mechanics parameters in the same data channel for comparison to determine the target rock mechanics parameters in the rock mechanics parameter conversion model; wherein the target rock mechanics parameters make the theoretical values ​​of the rock mechanics parameters match the core experimental test data; comparing the formation pressure test data with the theoretical values ​​of the rock mechanics parameters; The theoretical values ​​of formation pore pressure are placed in the same data channel for comparison to determine the target formation pore pressure parameters in the formation pore pressure model; wherein the target formation pore pressure key parameters make the formation pressure test data match the theoretical values ​​of formation pore pressure; the drilling-logging data and the theoretical values ​​of horizontal geostress are placed in the same data channel for comparison to determine the target tectonic stress coefficient in the geostress model; wherein the target tectonic stress coefficient makes the theoretical values ​​of horizontal geostress match the drilling-logging data; the target rock mechanics parameters, the target formation pore pressure parameters and the target tectonic stress coefficient are used as the first target key parameters of the pilot well.

[0077] Optionally, before correcting the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure and the theoretical values ​​of the horizontal ground stress respectively based on the actual drilling multi-source data, it also includes: depth homing the actual drilling multi-source data so that the depth posture of the actual drilling multi-source data matches the depth position in the logging curve of the pilot well.

[0078] In an embodiment of the present invention, since there is a depth error between the drill bit depth and the logging curve, when using the core experiment test results, actual drilling drilling fluid density, logging gas measurement anomalies, ground breaking experiments and complex downhole accidents (overflow, well leakage) and other actual drilling multi-source data for calibration and correction, the core experiment test results, actual drilling drilling fluid density, logging gas measurement anomalies, ground breaking experiments and complex downhole accidents (overflow, well leakage) and other actual drilling multi-source data are cored, and the multi-source data in the actual drilling process are reasonably placed at the correct depth position of the logging curve, so that the depth posture of the actual drilling multi-source data matches the depth position in the logging curve of the pilot well. If there are a lot of actual drilling multi-source data such as core experiment test results, actual drilling drilling fluid density, logging gas measurement anomalies, ground breaking experiments and complex downhole accidents (overflow, well leakage), some abnormal data points with large errors in testing or recording can be excluded first. Table 1 is a table of actual drilling multi-source data after depth homing provided by an embodiment of the present invention:

[0079] Table 1 Multi-source data table of actual drilling after depth homing

[0080]

[0081]

[0082]

[0083] In the embodiment of the present invention, the rock mechanics parameter test results in the core experiment after homing are placed in the same data channel for comparison with the theoretical values ​​of the rock mechanics parameters. Based on point data projection, the dynamic / static rock mechanics parameter conversion model parameter A is frequently adjusted. Ed-s , B Ed-s , and The main principle of making the theoretical value of the static rock mechanics parameter profile consistent with the rock mechanics parameter test results is to be as close as possible or transfer multiple sets of experimental test data points as a whole, so as to determine the actual value of the static rock mechanics parameter profile. Exemplarily, the target rock mechanics parameter in the rock mechanics parameter conversion model that makes the theoretical value of the rock mechanics parameter match the core experimental test data can be: Ed-s =0.9, B Ed-s =0.5, Figure 5 This is a projection diagram of the core experimental test data of a pilot well provided by an embodiment of the present invention and the theoretical values ​​of rock mechanics parameters. Table 2 is a data table of static rock mechanics parameter values ​​corresponding to a logging curve provided by an embodiment of the present invention:

[0084] Table 2 Data table of static rock mechanical parameter values ​​corresponding to logging curves

[0085]

[0086] In the embodiment of the present invention, the actual drilling fluid density, logging gas measurement anomalies, well leakage, overflow and formation pressure field test data after homing are placed in the same data channel for comparison with the theoretical value of formation pore pressure. Based on point data projection, the key parameters δ and β of the calculation model (formation pore pressure model) in the Bower method are frequently adjusted to make the theoretical value of formation pore pressure consistent with the calibration data. The main principle is to be as close as possible or transfer multiple groups of experimental test data points as a whole, so as to clarify the actual value of the formation pore pressure profile. Exemplarily, the target formation pore pressure parameters (i.e., the key parameters of the Bowers method calculation model) in the formation pore pressure model that matches the formation pressure test data with the theoretical value of formation pore pressure can be: δ=0.4, β=0.79. Figure 6 This is a projection diagram of the actual drilling multi-source data of the pilot well and the formation pore pressure profile value provided by the embodiment of the present invention. Table 3 is a data table of the pore pressure parameter value corresponding to a logging curve provided by the embodiment of the present invention:

[0087] Table 3 Data table of pore pressure parameter values ​​corresponding to logging curves

[0088]

[0089] In the embodiment of the present invention, the core test results, field ground breaking test data, well leakage data and other data are compared with the maximum and minimum horizontal ground stress theoretical values ​​in the same data channel by point data projection. By frequently adjusting the tectonic stress coefficient ε in the ground stress model, the tectonic stress coefficient ε is calculated. Hmax and ε Hmin , so that the maximum and minimum horizontal geostress theoretical values ​​are translated to be consistent with the calibration data, that is, the horizontal geostress theoretical values ​​are matched with the drilling-logging data in the actual drilling multi-source data. Among them, the main principle is to transfer multiple sets of experimental test data points as close as possible or as a whole, and finally determine the actual values ​​of the maximum and minimum horizontal geostress profiles. Exemplarily, the target tectonic stress coefficient in the geostress model that makes the horizontal geostress theoretical value match the drilling-logging data can be: ε Hmax =0.00055,ε Hmin =0.00005. Figure 7 A projection diagram of actual drilling multi-source data of a pilot well and theoretical values ​​of horizontal geostress profiles provided in an embodiment of the present invention. Figure 8 The actual value diagram of the horizontal geostress profile of the pilot well calibrated based on the actual drilling multi-source data provided by the embodiment of the present invention. Table 4 is a data table of horizontal geostress parameter values ​​corresponding to a logging curve provided by the embodiment of the present invention:

[0090] Table 4 Data table of horizontal geostress parameter values ​​corresponding to logging curves

[0091]

[0092] In the embodiment of the present invention, the target rock mechanics parameters, the target formation pore pressure parameters and the target tectonic stress coefficient are used as the first target key parameters of the pilot well.

[0093] S250. Under the premise of controlling the stratum of the pilot well to match the stratum of the horizontal well, in the process of performing logging stretching from the pilot well to the horizontal well based on the vertical depth offset between the vertical depth of the pilot well and the vertical depth of the horizontal well, determine the key parameter mapping relationship between the horizontal well and the pilot well.

[0094] S260. Determine a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter.

[0095] In the embodiment of the present invention, according to the key parameter mapping relationship between the horizontal well and the pilot well, the first target key parameter of the pilot well is converted into the second target key parameter of the horizontal well. Exemplarily, the dynamic and static conversion relationship parameters of the rock mechanics parameters of the horizontal well are: Ed-s =0.95, B Ed-s =0.52, The Bowers method for horizontal wells calculates the model parameters of formation pore pressure: δ = 0.45, β = 0.75. The combined spring model for horizontal wells calculates the model parameters of ground stress: ε H max =0.00058,ε H min =0.00006.

[0096] S270. Determine the reservoir horizontal geostress of the horizontal well according to the second target key parameter and the second logging data of the horizontal well.

[0097] In an embodiment of the present invention, based on the acoustic wave, density and other logging data of the horizontal well and the determined second target key parameters, the horizontal geostress of the reservoir of the horizontal well is determined by using the formation pore pressure, rock mechanics and geostress calculation model. Fig. 9 A reservoir horizontal geostress profile diagram of a horizontal well based on the geostress data mapping of a pilot well is provided in an embodiment of the present invention.

[0098] It should be noted that, in the above embodiment, E d represents the dynamic elastic modulus, ρ(z) represents the rock density, Δt p represents the time difference of longitudinal sound waves, Δt s represents the time difference of shear wave sound wave, μ d represents the dynamic Poisson's ratio, E s represents the dynamic elastic modulus, A Ed-s Indicates the conversion coefficient of dynamic and static elastic modulus 1, B Ed-s Indicates the conversion coefficient of dynamic and static elastic modulus2, μ s represents the static Poisson's ratio, Indicates the dynamic and static Poisson's ratio conversion factor 1, Indicates the dynamic and static Poisson's ratio conversion coefficient 2, V p represents the acoustic velocity, φ represents the internal friction angle, δ represents the Bowers method coefficient, β represents the Bowers method exponential coefficient, α represents the Biot coefficient, E represents the static Young's modulus of rock, υ represents the static Poisson's ratio of rock, σ V represents the overlying formation pressure, P p represents the formation pore pressure, σ h represents the minimum horizontal principal stress, ε H max The tectonic stress coefficient representing the direction of the maximum horizontal stress, ε H min The tectonic stress coefficient indicating the direction of minimum horizontal stress.

[0099] The reservoir geostress prediction method provided by the embodiment of the present invention calculates the theoretical value of the rock mechanical parameter profile of the formation based on the natural gamma, density, sonic and other logging data of the pilot well, adopts the density integration method and the combined spring model to calculate the theoretical value of the geostress, and uses the multi-source data such as the pilot well drilling-logging-testing as the calibration data to correct the theoretical value of the horizontal geostress, determine the actual value of the horizontal geostress, and clarify the key parameters involved in the geostress calculation model. Finally, the geostress state of the horizontal well reservoir is reasonably determined by using the geostress results of the pilot well through physical mapping, which is helpful to fully understand and finely describe the geomechanical characteristics of the shale reservoir in southern Sichuan, provide guidance for the optimization design of horizontal well drilling and hydraulic fracturing parameters, and improve shale gas production, which is of great significance to the development of deep shale gas resources in the Sichuan Basin.

[0100] Embodiment 3

[0101] Fig.10 This is a schematic diagram of the structure of a reservoir ground stress prediction device provided in Example 3 of the present invention. Fig.10 As shown, the device comprises:

[0102] A first target key parameter determination module 1010 is used to obtain first well logging data and actual drilling multi-source data of the pilot well, and determine the first target key parameter of the pilot well based on the first well logging data and the actual drilling multi-source data;

[0103] A key parameter mapping relationship determination module 1020 is used to determine the key parameter mapping relationship between the horizontal well and the pilot well;

[0104] A second target key parameter determination module 1030, configured to determine a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter;

[0105] The reservoir horizontal geostress determination module 1040 is used to determine the reservoir horizontal geostress of the horizontal well according to the second target key parameter and the second logging data of the horizontal well.

[0106] Optionally, the first target key parameter determination module includes:

[0107] a formation pore pressure theoretical value calculation unit, used to calculate the theoretical value of rock mechanics parameters of the pilot well, the theoretical value of overburden pressure and the theoretical value of formation pore pressure based on the first well logging data;

[0108] a horizontal geostress theoretical value determination unit, configured to determine the horizontal geostress theoretical value of the pilot well according to the rock mechanics parameter theoretical value, the overburden stratum pressure theoretical value and the stratum pore pressure theoretical value;

[0109] The first target key parameter determination unit is used to correct the theoretical value of the rock mechanics parameter, the theoretical value of the formation pore pressure and the theoretical value of the horizontal ground stress respectively based on the actual drilling multi-source data, and determine the first target key parameter of the pilot well during the correction process.

[0110] Optionally, the first logging data includes natural gamma logging data, density logging data and sonic logging data;

[0111] The formation pore pressure theoretical value calculation unit includes:

[0112] A rock mechanics parameter theoretical value calculation subunit, used for calculating the rock mechanics parameter theoretical value of the pilot well based on the natural gamma logging data and the sonic logging data;

[0113] An overburden formation pressure theoretical value calculation subunit, used to calculate the overburden formation pressure theoretical value of the pilot well based on the density logging data;

[0114] The formation pore pressure theoretical value calculation subunit is used to calculate the formation pore pressure theoretical value of the pilot well based on the acoustic logging data.

[0115] Optionally, the rock mechanics parameter theoretical value calculation subunit is used to:

[0116] Determining the lithology type of the pilot well based on the natural gamma logging data; wherein the lithology type includes shale and non-shale;

[0117] A rock mechanics parameter conversion model is determined according to the lithology type, and the theoretical values ​​of the rock mechanics parameters of the pilot well are calculated based on the natural gamma logging data, the sonic logging data and the rock mechanics parameter model.

[0118] Optionally, the actual drilling multi-source data includes drilling-logging data, formation pressure test data and core experiment test data;

[0119] Optionally, the first target key parameter determination unit is used to:

[0120] Placing the core experimental test data and the theoretical value of the rock mechanics parameter in the same data channel for comparison, so as to determine the target rock mechanics parameter in the rock mechanics parameter conversion model; wherein the target rock mechanics parameter makes the theoretical value of the rock mechanics parameter match the core experimental test data;

[0121] Placing the formation pressure test data and the formation pore pressure theoretical value in the same data channel for comparison to determine a target formation pore pressure parameter in a formation pore pressure model; wherein the target formation pore pressure key parameter makes the formation pressure test data match the formation pore pressure theoretical value;

[0122] Placing the drilling-logging data and the theoretical value of horizontal geostress in the same data channel for comparison to determine a target tectonic stress coefficient in the geostress model; wherein the target tectonic stress coefficient makes the theoretical value of horizontal geostress match the drilling-logging data;

[0123] The target rock mechanics parameters, the target formation pore pressure parameters and the target structural stress coefficient are used as the first target key parameters of the pilot well.

[0124] Optionally, also include:

[0125] The depth homing module is used to perform depth homing on the actual drilling multi-source data before respectively correcting the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure and the theoretical values ​​of the horizontal ground stress based on the actual drilling multi-source data, so that the depth posture of the actual drilling multi-source data matches the depth position in the logging curve of the pilot well.

[0126] Optionally, the key parameter mapping relationship determination module is used to:

[0127] Under the premise of controlling the stratum of the pilot well to match the stratum of the horizontal well, in the process of performing logging stretching from the pilot well to the horizontal well based on the vertical depth offset between the vertical depth of the pilot well and the vertical depth of the horizontal well, the key parameter mapping relationship between the horizontal well and the pilot well is determined.

[0128] The reservoir geostress prediction device provided in the embodiment of the present invention can execute the reservoir geostress prediction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0129] Embodiment 4

[0130] Fig.11A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0131] like Fig.11 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0132] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0133] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a reservoir geostress prediction method.

[0134] In some embodiments, the reservoir in-situ stress prediction method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the reservoir in-situ stress prediction method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the reservoir in-situ stress prediction method in any other appropriate manner (e.g., by means of firmware).

[0135] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0136] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0137] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0138] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0139] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0140] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0141] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0142] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A reservoir geostress prediction method, characterized in that: include: Acquire first well logging data and actual drilling multi-source data of the pilot well, and determine first target key parameters of the pilot well based on the first well logging data and the actual drilling multi-source data; Determine a key parameter mapping relationship between the horizontal well and the pilot well; Determining a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter; The horizontal geostress of the reservoir of the horizontal well is determined according to the second target key parameter and the second logging data of the horizontal well.

2. The method according to claim 1, characterized in that Determining the first target key parameter of the pilot well based on the first well logging data and the actual drilling multi-source data includes: Calculating theoretical values ​​of rock mechanics parameters, theoretical values ​​of overburden formation pressure, and theoretical values ​​of formation pore pressure of the pilot well based on the first well logging data; Determine the theoretical value of horizontal in-situ stress of the pilot well according to the theoretical value of the rock mechanics parameter, the theoretical value of the overburden stratum pressure and the theoretical value of the stratum pore pressure; Based on the actual drilling multi-source data, the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure and the theoretical values ​​of the horizontal ground stress are corrected respectively, and the first target key parameters of the pilot well are determined during the correction process.

3. The method according to claim 2, characterized in that The first logging data includes natural gamma logging data, density logging data and sonic logging data; Calculating the theoretical value of the rock mechanics parameter of the pilot well, the theoretical value of the overburden formation pressure, and the theoretical value of the formation pore pressure based on the first well logging data includes: Calculating theoretical values ​​of rock mechanics parameters of the pilot well based on the natural gamma logging data and the sonic logging data; Calculate the theoretical value of the overburden pressure of the pilot well based on the density logging data; The theoretical value of the formation pore pressure of the pilot well is calculated based on the sonic logging data.

4. The method according to claim 3, characterized in that Calculating the theoretical values ​​of rock mechanics parameters of the pilot well based on the natural gamma logging data and the sonic logging data includes: Determining the lithology type of the pilot well based on the natural gamma logging data; wherein the lithology type includes shale and non-shale; A rock mechanics parameter conversion model is determined according to the lithology type, and the theoretical values ​​of the rock mechanics parameters of the pilot well are calculated based on the natural gamma logging data, the sonic logging data and the rock mechanics parameter model.

5. The method according to claim 2, characterized in that: The actual drilling multi-source data includes drilling-logging data, formation pressure test data and core experiment test data; Based on the actual drilling multi-source data, the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure, and the theoretical values ​​of the horizontal ground stress are corrected respectively, and the first target key parameters of the pilot well are determined during the correction process, including: Placing the core experimental test data and the theoretical value of the rock mechanics parameter in the same data channel for comparison, so as to determine the target rock mechanics parameter in the rock mechanics parameter conversion model; wherein the target rock mechanics parameter makes the theoretical value of the rock mechanics parameter match the core experimental test data; Placing the formation pressure test data and the formation pore pressure theoretical value in the same data channel for comparison to determine a target formation pore pressure parameter in a formation pore pressure model; wherein the target formation pore pressure key parameter makes the formation pressure test data match the formation pore pressure theoretical value; Placing the drilling-logging data and the theoretical value of horizontal geostress in the same data channel for comparison to determine a target tectonic stress coefficient in the geostress model; wherein the target tectonic stress coefficient makes the theoretical value of horizontal geostress match the drilling-logging data; The target rock mechanics parameters, the target formation pore pressure parameters and the target structural stress coefficient are used as the first target key parameters of the pilot well.

6. The method according to claim 5, characterized in that Before respectively correcting the theoretical values ​​of the rock mechanics parameters, the theoretical values ​​of the formation pore pressure, and the theoretical values ​​of the horizontal ground stress based on the actual drilling multi-source data, the method further includes: The actual drilling multi-source data is depth-homed so that the depth position of the actual drilling multi-source data matches the depth position in the logging curve of the pilot well.

7. The method according to claim 1, characterized in that Determine the key parameter mapping relationship between the horizontal well and the pilot well, including: Under the premise of controlling the stratum of the pilot well to match the stratum of the horizontal well, in the process of performing logging stretching from the pilot well to the horizontal well based on the vertical depth offset between the vertical depth of the pilot well and the vertical depth of the horizontal well, the key parameter mapping relationship between the horizontal well and the pilot well is determined.

8. A reservoir ground stress prediction device, characterized in that: include: A first target key parameter determination module, used to obtain first well logging data and actual drilling multi-source data of the pilot well, and determine the first target key parameter of the pilot well based on the first well logging data and the actual drilling multi-source data; A key parameter mapping relationship determination module, used to determine the key parameter mapping relationship between the horizontal well and the pilot well; A second target key parameter determination module, used to determine a second target key parameter of the horizontal well based on the key parameter mapping relationship and the first target key parameter; The reservoir horizontal geostress determination module is used to determine the reservoir horizontal geostress of the horizontal well according to the second target key parameter and the second logging data of the horizontal well.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the reservoir in-situ stress prediction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the reservoir in-situ stress prediction method according to any one of claims 1 to 7 when executed.

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