Method and device for constructing reservoir prediction model based on seismic reflection interface characteristics and method and device for deploying well location by adopting reservoir prediction model, electronic equipment, storage medium and computer program product

Abstract

The invention relates to the technical field of exploration and development, and discloses a method and device for constructing a reservoir prediction model based on seismic reflection interface characteristics and deploying a well location by adopting the reservoir prediction model, electronic equipment, a storage medium and a computer program product. The method comprises the steps that based on seismic data or logging data of a target work area, a single-well target stratum seismic reflection coefficient of the target work area is obtained, and the single-well target stratum seismic reflection coefficient comprises a drilled target stratum seismic reflection coefficient; and constructing a reservoir prediction model based on the seismic reflection coefficient of the drilled target layer, the well logging data, the productivity data and the well logging data. The method is applied to prediction of various geological reservoirs, exploration and development work such as well location deployment can be guided through accurate prediction and positioning of the high-quality reservoirs, technical support is provided for exploration, cost is saved, and the exploration success rate is effectively promoted and improved.

Description

Technical Field

[0001] This invention relates to the field of exploration and development technology, and in particular to methods, apparatus, electronic devices, storage media and computer program products for constructing reservoir prediction models based on seismic reflection interface characteristics and deploying well locations using such models. Background Technology

[0002] Currently, in oil and gas field development, high-quality reservoir prediction technology primarily relies on geological modeling based on multi-parameter production data fitting analysis. This systematic analysis qualitatively or semi-quantitatively identifies potential high-quality reservoir areas to guide production practices. Examples include high-quality reservoir prediction and identification techniques based on graded configuration constraining low-permeability facies, and high-quality reservoir prediction based on sedimentary facies control. However, due to reservoir heterogeneity and the quality of seismic data, high-quality reservoir prediction suffers from multiple solutions. In contrast, high-quality reservoir prediction technologies in exploration are relatively fewer, and most rely on geophysical methods. The mainstream research focuses on unconventional oil and gas reservoirs, tight sandstone lithologic gas reservoirs, and special lithologic oil and gas reservoirs, employing geophysical methods for key technologies in identifying high-quality reservoirs.

[0003] Existing technologies for predicting high-quality reservoirs and formation pressure rely on the reservoir type and distribution of adjacent wells or adjacent areas at the same stratigraphic level, as well as the formation pressure of adjacent wells or adjacent areas at the same stratigraphic level, to predict the high-quality reservoirs and formation pressure of deployed wells.

[0004] The shortcomings of existing well placement technologies are as follows: For clastic rock exploration, existing technologies only predict structural traps, not reservoirs, and determine well locations at structural high points. However, some reservoirs are not located at structural high points, leading to incorrect well placement. For carbonate rock exploration, existing technologies assume the center of a string of beads is the reservoir center and place the target point there. However, in reality, high-quality carbonate reservoirs are located at one point on both sides of the string of beads. One point is a specific location in the middle of the string where a high-quality reservoir exists, and the two sides are the inner and outer interfaces of the string. The outer interface is the outer interface of the entire string, and the inner interface is the outer interface of the central area. The reservoir is most developed at the intersection of the inner and outer interfaces and the fault surface. Therefore, existing technologies cannot accurately predict the location of high-quality reservoirs, resulting in incorrect well placement. Existing technologies cannot accurately predict the formation pressure of the target layer, especially abnormally high pressure, which can easily lead to blowouts and other accidents. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method, apparatus, electronic device, storage medium, and computer program product for constructing a reservoir prediction model based on seismic reflection interface characteristics and deploying well locations accordingly. This model can effectively predict high-quality reservoirs and formation pressures, and allows for well location deployment based on the predicted results, providing technical support for exploration and significantly improving exploration success rates. The invention provides the following technical solution:

[0006] In a first aspect of the present invention, a method for constructing a reservoir prediction model based on seismic reflection interface characteristics is provided, the method comprising:

[0007] Based on the seismic data or well logging data of the target work area, obtain the seismic reflection coefficient of the target layer of a single well in the target work area, wherein the seismic reflection coefficient of the target layer of a single well includes the seismic reflection coefficient of the target layer of a drilled well.

[0008] Based on the seismic reflection coefficient of the target layer in the drilled well, along with well logging data, production data, and well logging data, a reservoir prediction model is constructed.

[0009] Furthermore, the logging data includes the highest and second highest gas measurement values ​​of the target formation that have been drilled; the production capacity data includes the unit production of the drilled well, the tubing pressure of the target formation, and the formation pressure.

[0010] Furthermore, the seismic reflection coefficients of the target layer in the drilled wells in the target work area are obtained, including:

[0011] Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers;

[0012] Based on the logging data of the target work area, obtain the volume density of the target reservoir section, the propagation velocity of the target reservoir section, the volume density of the target non-reservoir section, and the propagation velocity of the target non-reservoir section;

[0013] Based on the volumetric density of the target reservoir section, the propagation velocity of the target reservoir section, the volumetric density of the non-reservoir section of the target layer, and the propagation velocity of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer in the target work area is obtained.

[0014] Furthermore, based on the volumetric density of the target reservoir section, the propagation velocity of the target reservoir section, the volumetric density of the non-reservoir section of the target layer, and the propagation velocity of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer in the drilled wells in the target work area is obtained, including:

[0015] Based on the volume density and propagation velocity of the target reservoir segment, the wave impedance of the target reservoir segment is obtained;

[0016] Based on the volume density and propagation velocity of the non-reservoir section of the target layer, the wave impedance of the non-reservoir section of the target layer is obtained;

[0017] Based on the wave impedance of the target layer reservoir section and the wave impedance of the target layer non-reservoir section, the seismic reflection coefficient of the target layer in the drilled wells in the target work area is obtained.

[0018] Furthermore, obtaining the seismic reflection coefficients of the target layer in the drilled wells in the target work area also includes:

[0019] Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers;

[0020] Based on the seismic data of the target work area, obtain the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer in the drilled well;

[0021] Based on the wave impedance of the target layer reservoir section and the wave impedance of the target layer non-reservoir section, the seismic reflection coefficient of the target layer in the drilled wells in the target work area is obtained.

[0022] Furthermore, obtaining the seismic reflection coefficients of the target layers already drilled in the target work area also includes obtaining the seismic reflection coefficients of the target layers already drilled in the carbonate bead region: obtaining seismic profiles based on seismic data of the target work area;

[0023] Determine the location of the target layer bead in the drilling based on the seismic profile;

[0024] Based on the seismic data inversion of the target work area, the lowest wave impedance inside the string of beads and the wave impedance of the non-reservoir section around the string of beads are obtained.

[0025] Based on the lowest wave impedance inside the beads and the wave impedance of the non-reservoir section around the beads, the seismic reflection coefficient of the drilled target layer in the carbonate rock bead area is obtained.

[0026] Furthermore, the reservoir prediction model includes:

[0027] The relationships between the reflection coefficient of the drilled target formation and the porosity of the drilled well, the reflection coefficient of the drilled target formation and the gas measurement value of the drilled well, the reflection coefficient of the drilled target formation and the unit production of the drilled well, the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation, and / or the reflection coefficient of the drilled target formation and the formation pressure.

[0028] Furthermore, the relationship between the reflection coefficient of the drilled target layer and the porosity of the drilled well is as follows:

[0029] y1 = a1x1 + b1

[0030] Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or,

[0031] The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows:

[0032] y2=a2x2+b2

[0033] Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or,

[0034] The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows:

[0035] y3 = a3x3 + b3

[0036] Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or,

[0037] The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows:

[0038] y4 = a4x4 + b4

[0039] Where y4 is the reflection coefficient of the drilled target formation related to the tubing pressure of the drilled target formation, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or,

[0040] The relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure in the drilled well is as follows:

[0041] y5 = a5x5 + b5

[0042] Where y5 is the reflection coefficient of the drilled target layer related to the drilled formation pressure, x5 is the drilled formation pressure, and a5 and b5 are constants.

[0043] In a second aspect of the invention, a method for deploying well locations is provided, utilizing a reservoir prediction model constructed as described above, the method comprising:

[0044] Based on the seismic data of the target work area, the seismic reflection coefficient of the target layer of a single well in the target work area is obtained, and the seismic reflection coefficient of the target layer of the single well includes the seismic reflection coefficient of the target layer of the deployed well.

[0045] Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted.

[0046] Under the condition of having a trap, the well location is deployed based on the reservoir development status and formation pressure prediction results of the deployment well.

[0047] Furthermore, obtaining the seismic reflection coefficient of the target layer for the wells deployed in the target work area also includes:

[0048] Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers;

[0049] Based on the seismic data of the target work area, obtain the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer of the deployed well;

[0050] Based on the wave impedance of the reservoir section and the wave impedance of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer of the well deployed in the target work area is obtained.

[0051] Furthermore, based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted, including:

[0052] Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure and / or formation pressure of the target layer of the deployed well are predicted.

[0053] Based on the highest and second highest gas measurement values ​​corresponding to the target layer of the deployed well, the reservoir development status of the target layer of the deployed well is predicted by porosity and unit production.

[0054] Based on the target layer tubing pressure and formation pressure corresponding to the target layer of the deployed well, the formation pressure of the target layer of the deployed well is predicted.

[0055] Furthermore, based on the reservoir development status and formation pressure prediction results of the deployed wells, the well locations are determined, including:

[0056] The reservoir development status of the deployed well is a high-quality reservoir, and the well location is as follows;

[0057] The reservoir development status of the deployed well is poor, so no well site is deployed.

[0058] Furthermore, when the reservoir development of the deployed well is a high-quality reservoir, if the predicted formation pressure is higher than the threshold, a drilling fluid that can balance the formation pressure should be selected during the well deployment process.

[0059] In a third aspect of the invention, an apparatus for constructing a reservoir prediction model based on seismic reflection interface characteristics is provided, the apparatus comprising:

[0060] The first acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target area based on the seismic data or well logging data of the target area. The seismic reflection coefficient of the single well in the target area includes the seismic reflection coefficient of the target layer that has been drilled.

[0061] The construction unit is used to construct a reservoir prediction model based on the seismic reflection coefficient of the target layer of the drilled well, as well as logging data, production data, and well logging data.

[0062] Furthermore, the reservoir prediction model includes:

[0063] The relationships between the reflection coefficient of the drilled target formation and the porosity of the drilled well, the reflection coefficient of the drilled target formation and the gas measurement value of the drilled well, the reflection coefficient of the drilled target formation and the unit production of the drilled well, the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation, and the reflection coefficient of the drilled target formation and the formation pressure are given.

[0064] The relationship between the reflection coefficient of the target formation in a drilled well and the porosity of the drilled well is as follows:

[0065] y1 = a1x1 + b1

[0066] Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or,

[0067] The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows:

[0068] y2=a2x2+b2

[0069] Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or,

[0070] The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows:

[0071] y3 = a3x3 + b3

[0072] Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or,

[0073] The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows:

[0074] y4 = a4x4 + b4

[0075] Where y4 is the reflection coefficient of the drilled target formation related to the unit production of the drilled well, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or,

[0076] The relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure in the drilled well is as follows:

[0077] y5 = a5x5 + b5

[0078] Where y5 is the reflection coefficient of the drilled target layer related to the drilled formation pressure, x5 is the drilled formation pressure, and a5 and b5 are constants.

[0079] In a fourth aspect of the invention, an apparatus for deploying well locations is provided, utilizing a reservoir prediction model constructed using the method described above, characterized in that the apparatus comprises:

[0080] The second acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target work area based on the seismic data of the target work area. The seismic reflection coefficient of a single well in the target layer includes the seismic reflection coefficient of the target layer of the deployment well.

[0081] The prediction unit is used to predict the reservoir development status and formation pressure of the deployed wells in the target work area based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well.

[0082] Deployment unit, used to deploy well locations based on reservoir development status and formation pressure prediction results of the deployment well.

[0083] Furthermore, based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted, including:

[0084] Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure and / or formation pressure of the target layer of the deployed well are predicted.

[0085] Based on the highest and second highest gas measurement values, porosity, and unit production of the target layer of the deployed well, the reservoir development status of the target layer of the deployed well is predicted.

[0086] Based on the target layer tubing pressure and formation pressure corresponding to the target layer of the deployed well, the formation pressure of the target layer of the deployed well is predicted.

[0087] Furthermore, based on the reservoir development status and formation pressure prediction results of the deployed wells, the well locations are determined, including:

[0088] The reservoir development status of the deployed well is a high-quality reservoir, and the well location is as follows;

[0089] The reservoir development status of the deployed well is poor, so no well site is deployed.

[0090] In a fifth aspect of the invention, an electronic device is provided, the electronic device comprising at least one processor and at least one memory, the memory being data-connected to the processor, wherein...

[0091] The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method described above.

[0092] In a sixth aspect of the invention, a computer-storeable medium is provided, characterized in that the storage medium stores computer instructions, which, when executed by a processor, specifically perform the steps in the above-described method.

[0093] In a seventh aspect of the invention, a computer program product is provided, comprising computer instructions, characterized in that, when the computer instructions are executed by a processor, they specifically perform the steps in the above-described method.

[0094] The technical effects and advantages of this invention are as follows:

[0095] This invention utilizes seismic reflection coefficients to predict high-quality reservoirs and formation pressure. The model involves few parameters, is highly operable, has low systematic error, and can provide quantitative results for potential exploration areas in advance. Furthermore, the reflection coefficient primarily reflects interface changes, precisely reflecting variations at the top and bottom interfaces of strong reflection axes in clastic rocks or the beaded interfaces in carbonate rocks, making it easier to identify high-quality reservoirs than amplitude bright spots.

[0096] The prediction method of this invention can be applied to the prediction of various geological reservoirs, including carbonate rocks and clastic rocks. By accurately predicting and locating high-quality reservoirs, it can help guide exploration and development work such as well site deployment, provide technical support for exploration, save costs, and effectively promote and improve the success rate of exploration.

[0097] The prediction method of this invention can be applied to the prediction of formation pressure in the target exploration layer. It can be applied to both carbonate rocks and clastic rocks. By accurately predicting formation pressure, especially the abnormally high pressure in the target exploration layer, a drilling fluid density that is balanced or slightly higher than the abnormally high pressure can be designed. This balances or slightly exceeds the formation pressure, ensuring drilling safety, providing technical support for exploration, saving costs, and effectively promoting and improving the exploration success rate.

[0098] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0099] Figure 1 This is a flowchart of a reservoir prediction model based on seismic reflection interface features and a method for deploying wells using it, provided in an embodiment of this application.

[0100] Figure 2 This is a diagram of a reservoir prediction model based on seismic reflection interface features and a device for deploying wells using it, provided in an embodiment of this application.

[0101] Figure 3aThe Cretaceous earthquake dual reflection features provided in the embodiments of this application;

[0102] Figure 3b The non-reflective banding characteristics of the Cretaceous Bashkichik Formation provided in the embodiments of this application;

[0103] Figure 3c The single reflectance feature of the Cretaceous system provided in the embodiments of this application;

[0104] Figure 4 The relationship between the reflection coefficient and the highest and second-highest gas measurement values ​​of drilled wells is provided in the embodiments of this application;

[0105] Figure 5 The relationship between reflection coefficient and porosity is provided for embodiments of this application;

[0106] Figure 6 The relationship between reflection coefficient and unit yield is provided for the embodiments of this application;

[0107] Figure 7 The relationship between reflection coefficient and oil pressure is provided in the embodiments of this application;

[0108] Figure 8 The clastic reservoir distribution pattern provided in the embodiments of this application;

[0109] Figure 9 Seismic reflection map of the Cretaceous system provided in the embodiments of this application;

[0110] Figure 10 Seismic reflection map of the Cretaceous system provided in the embodiments of this application;

[0111] Figure 11 The trajectory diagram of well G provided in the embodiments of this application;

[0112] Figure 12 The original design and actual drilling trajectory diagram of well H provided for the embodiments of this application;

[0113] Figure 13 The relationship between the reflection coefficient and the porosity of the drilled well is provided in the embodiments of this application;

[0114] Figure 14 The relationship between the reflection coefficient and the measured gas value from the drilled well is provided in the embodiments of this application;

[0115] Figure 15 The relationship between the reflection coefficient and the daily oil production equivalent (6mm nozzle) of the drilled well is provided for the embodiments of this application;

[0116] Figure 16 The relationship between the reflection coefficient and the oil pressure (6mm nozzle) of the drilled well is provided for the embodiments of this application;

[0117] Figure 17 The relationship between the reflection coefficient and the shut-in oil pressure of a 6mm nozzle in a drilled well is provided in the embodiments of this application;

[0118] Figure 18 The relationship between the reflection coefficient and the formation pressure of the drilled well is provided in the embodiments of this application;

[0119] Figure 19 A diagram illustrating the crack development pattern provided in an embodiment of this application;

[0120] Figure 20 This is a diagram illustrating the distribution pattern of a beaded reservoir with fractured solutions, provided in an embodiment of this application.

[0121] Figure 21 The relationship between reflection coefficient and formation pressure calculated from the seismic data volume inversion provided in the embodiments of this application;

[0122] Figure 22 A comparison diagram of predicted and actual reservoirs in well M provided for embodiments of this application;

[0123] Figure 23 This application provides a high-quality reservoir prediction map for N reservoirs in an embodiment.

[0124] Figure 24 This is a block diagram of an electronic device structure according to an embodiment of this application. Detailed Implementation

[0125] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0126] To address the shortcomings of existing technologies, this invention discloses a method for constructing a reservoir prediction model based on seismic reflection interface characteristics and for deploying well locations using this model, such as... Figure 1 As shown, the method includes,

[0127] Step 1: Based on the seismic data or well logging data of the target work area, obtain the seismic reflection coefficient of the target layer of a single well in the target work area. The seismic reflection coefficient of the target layer of a single well includes the seismic reflection coefficient of the target layer of the drilled well and the seismic reflection coefficient of the target layer of the deployed well.

[0128] Step 2: Based on the seismic reflection coefficient of the target layer in the drilled wells, along with logging data, production data, and well logging data, construct a reservoir prediction model; wherein, the logging data includes the highest and second highest gas measurement values ​​of the target layer in the drilled wells; the production data includes the unit production of the drilled wells, the tubing pressure of the target layer, and the formation pressure;

[0129] Step 3: Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, predict the reservoir development status and formation pressure of the deployed well in the target work area;

[0130] Step 4: Deploy well locations based on the reservoir development status and formation pressure prediction results of the deployment wells.

[0131] In a specific embodiment of the present invention, step 1, obtaining the seismic reflection coefficient of the target layer in the drilled well in the target work area, includes:

[0132] Select the highest and second-highest gas logging values ​​of each well in the target work area from the logging data. The highest and second-highest gas logging values ​​of the drilled wells are basically consistent with the seismic reflection axis depth of the target layer. The highest and second-highest gas logging values ​​of the drilled wells are set as the target layer. The relative value of the gas logging value ranges from 0.5 to the highest gas logging value.

[0133] Based on the logging data of the target work area, the volumetric density of the target reservoir section, the propagation velocity of the target reservoir section, the volumetric density of the target non-reservoir section (tight layer), and the propagation velocity of the target non-reservoir section (tight layer) are obtained. In a specific implementation of the present invention, the target layer includes reservoir sections and non-reservoir sections, wherein the non-reservoir section is also called a tight layer. For example, the section where fractures and cavities are located in carbonate rocks is a non-reservoir section, and the section where clastic rocks, mudstone, or tight sandstone are located is a non-reservoir section.

[0134] Based on the bulk density and propagation velocity of the target reservoir segment, the reservoir wave impedance of the top and bottom of the seismic reflection axis or the carbonate beaded reservoir is calculated.

[0135] Based on the volume density and propagation velocity of the non-reservoir section of the target layer, the wave impedance of the non-reservoir section of the target layer is calculated.

[0136] Based on the wave impedance of the reservoir section and the non-reservoir section of the target layer, the seismic reflection coefficient of the drilled target layer in the target work area is obtained. The formula for the seismic reflection coefficient of the drilled target layer in the target work area is expressed as:

[0137] r = (m1v1 - m2v2) / (m1v1 + m2v2), where m1 represents the volume density of the target reservoir segment, v1 represents the propagation velocity of the target reservoir segment, m2 represents the volume density of the non-reservoir segment of the target layer, and v2 represents the propagation velocity of the non-reservoir segment of the target layer; or,

[0138] Based on the seismic data of the target work area, the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer in the drilled well are directly obtained; based on the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer in the drilled well in the target work area is obtained.

[0139] In a specific embodiment of the present invention, obtaining the seismic reflection coefficient of the target layer that has been drilled in the target work area further includes obtaining the seismic reflection coefficient of the target layer that has been drilled in the carbonate bead region, which includes the following steps: obtaining a seismic profile based on the seismic data of the target work area;

[0140] Determine the location of the target layer bead in the drilling based on the seismic profile;

[0141] Based on the seismic data inversion of the target work area, the lowest wave impedance inside the string of beads and the wave impedance of the non-reservoir section around the string of beads are obtained.

[0142] Based on the lowest wave impedance inside the beads and the wave impedance of the non-reservoir section around the beads, the seismic reflection coefficient of the drilled target layer in the carbonate rock bead area is obtained.

[0143] In a specific embodiment of the present invention, step 1, obtaining the seismic reflection coefficient of the target layer of the well in the target work area, includes:

[0144] Select the highest and second highest gas logging values ​​of each drilled well in the target work area from the logging data. Since the depth of the highest and second highest gas logging values ​​of the drilled well is basically consistent with the seismic reflection axis depth of the target layer, the highest and second highest gas logging values ​​of the drilled well are set as the target layer.

[0145] Based on the seismic data of the target work area, the wave impedance of the target layer reservoir segment and the wave impedance of the target layer non-reservoir segment of the deployed well are obtained; based on the wave impedance of the target layer reservoir segment and the wave impedance of the target layer non-reservoir segment of the target layer, the seismic reflection coefficient of the target layer of the deployed well in the target work area is obtained.

[0146] In a specific embodiment of the present invention, for step 2, the reservoir prediction model includes: the relationship between the reflection coefficient of the drilled target layer and the porosity of the drilled well; the relationship between the reflection coefficient of the drilled target layer and the gas measurement value of the drilled well; the relationship between the reflection coefficient of the drilled target layer and the unit production of the drilled well; the relationship between the reflection coefficient of the drilled target layer and the tubing pressure of the drilled target layer; and the relationship between the reflection coefficient of the drilled target layer and the formation pressure, wherein...

[0147] The relationship between the reflection coefficient of the target formation in a drilled well and the porosity of the drilled well is as follows:

[0148] y1 = a1x1 + b1

[0149] Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or,

[0150] The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows:

[0151] y2=a2x2+b2

[0152] Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or,

[0153] The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows:

[0154] y3 = a3x3 + b3

[0155] Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or,

[0156] The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows:

[0157] y4 = a4x4 + b4

[0158] Where y4 is the reflection coefficient of the drilled target formation related to the tubing pressure of the drilled target formation, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or,

[0159] The relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure in the drilled well is as follows:

[0160] y5 = a5x5 + b5

[0161] Where y5 is the reflection coefficient of the drilled target layer related to the drilled formation pressure, x5 is the drilled formation pressure, and a5 and b5 are constants.

[0162] Predicting high-quality reservoirs and formation pressure using seismic reflection coefficients is highly advantageous due to the small number of parameters involved in the reservoir prediction model, its strong operability, low systematic error, and the ability to provide quantitative results of exploration potential areas in advance. Since the reflection coefficient primarily reflects interface changes, it precisely reflects the changes in the top and bottom interfaces of clastic rocks with strong reflection axes or the beaded interfaces of carbonate rocks, making it easier to identify high-quality reservoirs than amplitude bright spots. This is combined with a distribution pattern diagram of beaded carbonate rock fracture-dissolution reservoirs (…). Figure 20 High-quality reservoirs are distributed at the inner and outer interfaces of the clastic rock formation, with the most developed reservoirs located at the intersections of the inner and outer interfaces and faults. Clastic rock reservoir distribution pattern ( Figure 8 The yellow area in the diagram represents the upper and lower interfaces of the seismic reflection axis, where the reservoir is most developed. These two reservoir development models are derived based on a combination of actual drilling data and seismic reflection characteristics. The seismic reflection coefficient can be obtained from well logging data or seismic inversion. Well logging data and production data include the highest and second highest gas logging values, unit production, and target layer tubing pressure in drilled wells. Well logging data is obtained from geological logging, and production data is obtained from experimental production assessments.

[0163] In some specific embodiments of the present invention, for new blocks lacking seismic data, logging data, or / and production capacity data, data from neighboring blocks with similar geological conditions can be borrowed; or existing maps with similar geological conditions in adjacent blocks can be borrowed, reflection coefficients can be obtained through seismic inversion, and corresponding porosity data and formation pressure values ​​can be read by borrowing the maps.

[0164] In some embodiments of the present invention, for oil and gas producing wells, the production capacity data is the oil testing data, which includes the oil testing pressure, the oil and gas production equivalent over a predetermined time period, and the formation pressure, etc.

[0165] In a specific embodiment of the present invention, step 3, which involves predicting the reservoir development state and formation pressure of the deployed well in the target work area based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, includes:

[0166] Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure, and formation pressure are predicted for the target layer of the deployed well. When the deployed well is an oil or gas producing well, the unit production includes daily oil equivalent, monthly oil equivalent, annual oil equivalent, daily gas equivalent, monthly gas equivalent, and annual gas equivalent for a predetermined time period. When the deployed well is a water producing well, the unit production includes daily water equivalent, monthly water equivalent, and annual water equivalent for a predetermined time period. For single oil and gas producing wells, the target layer tubing pressure is the residual pressure after the flowing pressure lifts the oil and gas from the bottom of the well through the tubing to the wellhead, referred to as oil pressure, or test oil pressure.

[0167] Specifically, based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas logging values, porosity, unit production, target layer tubing pressure, and / or formation pressure of the target layer are predicted; based on the highest and second highest gas logging values, porosity, and unit production of the target layer of the deployed well, the reservoir development state of the target layer of the deployed well is predicted; based on the target layer tubing pressure and formation pressure of the target layer of the deployed well, the formation pressure of the target layer of the deployed well is predicted. The prediction results are as follows:

[0168] When the reservoir development of the deployed well is of high quality, a specific well location is selected; when the reservoir development of the deployed well is of poor quality, no well location is selected.

[0169] If the reservoir development of the deployed well is a high-quality reservoir, and the predicted formation pressure is higher than the threshold, it indicates that there is abnormal high pressure in the formation. The design of the deployed well should be based on drilling fluid that can balance or slightly exceed the abnormal high pressure to ensure drilling safety.

[0170] Based on the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure and formation pressure corresponding to the target layer of the deployed well, the reservoir development status of the target layer of the deployed well is analyzed.

[0171] For carbonate rocks, the lowest wave impedance of the entire bead and the highest wave impedance of the non-reservoir section of the target layer around the bead are calculated from the seismic data volume inversion. This allows for the calculation of the highest reflection coefficient of the bead. The location of the highest reflection coefficient may indicate the location of a cavern. Calculations show that the reflection coefficient of high-pressure wells is greater than 0.13. By comparing this data, it can be determined whether high pressure exists in the deployed well, allowing for appropriate measures to ensure downhole safety. This innovative achievement more accurately predicts high-quality reservoirs and cavern locations than existing technologies. Once the cavern location is determined, the wellbore trajectory can be close to the cavern without drilling through it, thus avoiding abnormal high pressure and significantly reducing safety risks.

[0172] This invention utilizes seismic reflection coefficients to predict high-quality reservoirs and formation pressure. The model involves few parameters, is highly operable, has low systematic error, and can provide quantitative results for potential exploration areas in advance. Furthermore, the reflection coefficient primarily reflects interface changes, precisely reflecting variations at the top and bottom interfaces of strong reflection axes in clastic rocks or the beaded interfaces in carbonate rocks, making it easier to identify high-quality reservoirs than amplitude bright spots.

[0173] The prediction method of this invention can be applied to the prediction of various geological reservoirs. It can predict reservoirs and formation pressure under different pressure systems and structures. It can be applied not only to carbonate rocks but also to clastic rocks. By accurately predicting and locating high-quality reservoirs, it can help guide exploration and development work such as well site deployment, provide technical support for exploration, save costs, and effectively promote and improve the success rate of exploration.

[0174] This invention also provides an apparatus for constructing a reservoir prediction model based on seismic reflection interface characteristics, such as... Figure 2 As shown, the device includes,

[0175] The first acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target area based on the seismic data or well logging data of the target area. The seismic reflection coefficient of the single well in the target area includes the seismic reflection coefficient of the target layer that has been drilled.

[0176] The second acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target work area based on the seismic data of the target work area. The seismic reflection coefficient of a single well in the target layer includes the seismic reflection coefficient of the target layer of the deployment well.

[0177] The construction unit is used to construct a reservoir prediction model based on the seismic reflection coefficient of the drilled target layer and logging data, production data, and well logging data; wherein, the logging data includes the highest and second highest gas measurement values ​​of the drilled target layer; the production data includes the unit production of the drilled well, the tubing pressure of the target layer, and the formation pressure;

[0178] The prediction unit is used to predict the reservoir development status and formation pressure of the deployed wells in the target work area based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well.

[0179] Deployment unit, used to deploy well locations based on reservoir development status and formation pressure prediction results of the deployment well.

[0180] In one specific embodiment of the present invention, the reservoir prediction model includes:

[0181] The relationships between the reflection coefficient of the drilled target formation and the porosity of the drilled well, the reflection coefficient of the drilled target formation and the gas measurement value of the drilled well, the reflection coefficient of the drilled target formation and the unit production of the drilled well, the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation, and the reflection coefficient of the drilled target formation and the formation pressure are given.

[0182] The relationship between the reflection coefficient of the target formation in a drilled well and the porosity of the drilled well is as follows:

[0183] y1 = a1x1 + b1

[0184] Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or,

[0185] The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows:

[0186] y2=a2x2+b2

[0187] Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or,

[0188] The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows:

[0189] y3 = a3x3 + b3

[0190] Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or,

[0191] The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows:

[0192] y4 = a4x4 + b4

[0193] Where y4 is the reflection coefficient of the drilled target formation related to the tubing pressure of the drilled target formation, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or,

[0194] The relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure in the drilled well is as follows:

[0195] y5 = a5x5 + b5

[0196] Where y5 is the reflection coefficient of the drilled target layer related to the drilled formation pressure, x5 is the drilled formation pressure, and a5 and b5 are constants.

[0197] Regarding the apparatus in the above embodiments, the specific manner in which each unit performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0198] Currently, well placement in clastic rocks mostly considers only the importance of local structures, without predicting high-quality reservoirs. This invention utilizes a seismic reflection system in conjunction with high-quality reservoirs and formation pressure for prediction. The model involves fewer parameters, is highly operable, has low systematic error, and can provide quantitative results for potential exploration areas in advance. Furthermore, the reflection coefficient primarily reflects interface changes, precisely reflecting the changes at the top and bottom interfaces of strong reflection axes in clastic rocks or the beaded interfaces in carbonate rocks. This makes it easier to identify high-quality reservoirs than amplitude bright spots, enabling precise location of high-quality reservoirs, providing technical support for exploration, and effectively promoting and improving the exploration success rate.

[0199] The technical solution of the present invention will be further described below with reference to specific embodiments.

[0200] Example 1

[0201] High-quality reservoirs: are considered to have key characteristics of double-reflection bands ( Figure 3a () or a single reflective stripe that is long laterally, thick longitudinally, and has a clear reflective stripe. Figure 3c It is a high-quality, large-scale reservoir.

[0202] Poor reservoirs: Reservoirs with single reflective bands that are short laterally, thin vertically, and have blurred or no reflective bands are considered poor reservoirs. Figure 3b ).

[0203] Wells that successfully or unsuccessfully discovered Cretaceous reservoirs with seismic reflection characteristics generally yielded high production, while those without reflection characteristics had poor reservoir quality and low production. For example ( Figure 3a This well, a Cretaceous formation, exhibits dual-reflection characteristics and a long lateral extension, indicating a high-quality reservoir. High production was achieved upon completion and testing. Another well ( Figure 3bThe Cretaceous reflection axis is blurry and short or lacks seismic reflection characteristics, indicating poor reservoir quality and no production capacity achieved during oil testing. Further calculations comparing the top and bottom depths of the seismic reflection axis with the best-performing gas logging section revealed that the top and bottom depths of the seismic reflection axis are basically consistent with the best oil and gas indication depths of the well. In a certain area, the seismic reflection axis depth of well A, after drilling 1, differs from the gas logging indication depth by 10-13m, with a gas logging yield of 13.15%. In well B, the top reflection axis depth of the Cretaceous strata differs from the gas logging indication section depth by 10-12m, with a total gas logging yield of 50.74%. The top depth of the first reflection axis within the Cretaceous strata differs from the gas logging indication section depth by 8-15m, with a total gas logging yield of 45.12%. The bottom depth of the first reflection axis within the Cretaceous strata differs from the gas logging indication section depth by 1-3m, with a total gas logging yield of 40.23%. The gas logging indication section and the top and bottom depths of the reflection axis are very consistent. Calculations were performed on more than 30 wells, and all conformed to this characteristic. This indicates that the top and bottom of the seismic reflection axis are where clastic rock reservoirs are most developed; simply put, the reservoirs on both sides of one axis of the clastic rock are most developed.

[0204] The relationship between seismic reflection coefficient and the highest and second highest gas measurement values, unit production, and tubing pressure of the target layer in drilled wells was established, demonstrating that the reflection coefficient can predict high-quality reservoirs.

[0205] The highest and second-highest gas logging values ​​in drilled wells were selected from geological logging data. These wells generally coincided with the depth of the Cretaceous seismic reflection axis. The wave impedance corresponding to these highest and second-highest gas logging values ​​was calculated, thus determining the wave impedance of the seismic reflection axis. The highest and second-highest gas logging values ​​corresponded to the reservoir wave impedance (m1v1), while the tight mudstone corresponded to the non-reservoir wave impedance of the target layer (m2v2). Using the reflection coefficient r = (m1v1 - m2v2) / (m1v1 + m2v2), where m1 represents the bulk density of the high-quality reservoir section of the target layer, v1 represents the propagation velocity of the high-quality reservoir section of the target layer, m2 represents the bulk density of the non-reservoir section of the target layer, and v2 represents the propagation velocity of the non-reservoir section of the target layer (where m1, v1, m2, and v2 can be obtained from logging data), the reflection coefficient of the drilled wells was calculated. The aim was to explore the relationship between the seismic reflection coefficient of the drilled wells and the highest and second-highest gas logging values, as well as the relationship between the reflection coefficient and the porosity of the high-quality reservoir in the drilled wells. Figure 4 The vertical axis represents the seismic reflection coefficient, and the horizontal axis represents the highest and second-highest gas measurement values ​​from drilled wells. A linear function is fitted: y = 0.0019x + 0.0315, r 2 =0.802, according to the judgment criteria, r 2A value >0.8 (this formula is applicable within the same block; for new blocks, new relationships can be established using this method based on the data from those new blocks; specific problems require specific analysis) indicates that the model has a high goodness of fit. The figure shows a positive correlation between the seismic reflection coefficient of drilled wells and the highest and second-highest gas detection values. In other words, a larger reflection coefficient indicates stronger seismic reflection and higher gas detection values, suggesting a better reservoir. The figure also shows that if the reflection coefficient is 0, there are no reflection characteristics and no gas detection values, indicating a poor reservoir. To verify the correctness of this judgment, a relationship between the reflection coefficient and the porosity of drilled wells was established, such as... Figure 5 The vertical axis represents the reflection coefficient, and the horizontal axis represents porosity. A linear function y = 0.0097x - 0.0229 is fitted, r = ... 2 =0.8557, according to the judgment criteria, r 2 A value greater than 0.8 indicates that the model has a high goodness of fit. The figure shows that the seismic reflection coefficient of the drilled well is directly proportional to the porosity. An increase in the reflection coefficient indicates an increase in the porosity of the drilled well. Increased porosity means that the reservoir is improving. The seismic reflection coefficient and porosity are related to the highest and second-highest gas measurement values ​​of the drilled well. An increase in the reflection coefficient indicates an increase in porosity and an increase in the highest and second-highest gas measurement values ​​of the drilled well.

[0206] Establish the relationship between reflection coefficient and daily oil and gas equivalent (unit output). Figure 6 According to this figure, clastic reservoirs can be divided into two main categories: those with a reflection coefficient less than 0.1 are low-porosity fractured reservoirs, and those with a reflection coefficient greater than 0.1 are porous reservoirs. For low-porosity fractured reservoirs, there are two further cases: the first case involves low porosity and highly developed fractures. Figure 6 Offline), the second scenario ( Figure 6 The middle line has relatively high porosity and well-developed cracks, mainly based on... Figure 5 The reflection coefficient is proportional to the porosity of the drilled well. The porosity in the first case is relatively lower than that in the second case. Figure 6 Although the porosity of the middle line is relatively high, the fractures are not as developed as in the first case. This clearly demonstrates that, under the same reflection coefficient, the daily oil and gas equivalent (unit production) in the first case is higher than that in the second case. (Reflection coefficient higher than 0.1) Figure 6 (On the upper limit), the daily oil and gas equivalent (unit production) corresponding to the line has a high reflection coefficient. However, some of the daily oil and gas equivalent (unit production) on this line is not as high as the daily oil and gas equivalent (unit production) corresponding to the low reflection coefficient of low-porosity fractured reservoirs. The main reason is that low-porosity fractured reservoirs are better than porous reservoirs. This is significantly different from the prediction of carbonate reservoirs, where a higher reflection coefficient indicates a better reservoir. From the relationship between reflection coefficient and oil pressure ( Figure 7A reflection coefficient greater than 0.1 indicates significant oil pressure variations, primarily related to reservoir changes. In other words, a higher reflection coefficient generally indicates a better reservoir and higher production. Figure 6 The higher the oil pressure, the better. The reflection coefficient is less than 0.1. Selection is based on the abundance of fractures. Figure 7 Which line has the most breaks and cracks? Choose... Figure 7 The lower limit, if there are fewer breaks, there will be fewer cracks, choose Figure 7 The midline of the curve also differs from the pressure prediction of carbonate formations. Therefore, the reflection coefficient can be used to predict the pressure of clastic formations.

[0207] from Figure 4 It is known that, based on actual drilling data, Well C has a reflection coefficient of 0.01086 and a gas yield of 0.72%, resulting in low production. Well D (Bozih) has a reflection coefficient of 0.015053, a gas yield of 0.747%, and a porosity of 3.6%, resulting in high production. For unconventional clastic rocks, a reflection coefficient greater than 0.015, a gas yield greater than 0.75%, and a porosity greater than 3.6% can result in high production. For conventional clastic rocks, specifically in region 2, the reason for the scarcity of high-yield wells is that the already drilled wells have very low reflection coefficients. Figure 6 To achieve high production, porosity must be greater than 11%, reflection coefficient greater than 0.1, and gas detection value greater than 30%. Before determining the well location, the reflection coefficient can be calculated. For conventional clastic rocks, the reflection coefficient must be greater than 0.1, and for unconventional clastic rocks, the reflection coefficient must be greater than 0.015 to meet the conditions for high production.

[0208] from Figure 5 Based on this, rocks with a porosity below 11% are classified as unconventional clastic rocks, applicable to the Bozi, Dabei, and Keshen areas. Rocks with a porosity above 11% are classified as conventional clastic rocks, applicable to the Zhongqiu area.

[0209] according to Figure 7 The relationship between the reflection coefficient and the test oil pressure (target layer tubing pressure) can be used to predict the pressure in clastic rock formations.

[0210] Clastic reservoir distribution patterns Figure 8 In the figure, the yellow part represents the upper and lower interfaces of the seismic reflection axis, where the reservoir is most developed. Based on the actual drilling situation and the seismic reflection characteristics, these two reservoir development models are obtained.

[0211] The reflection coefficient is used to guide well placement. The reflection coefficient primarily reflects the strength of interface reflection. Parameters such as porosity, gas logging values, daily oil and gas equivalent (unit production) during oil testing, and oil pressure (target layer tubing pressure) reflect the quality of clastic reservoirs. The reflection coefficient is directly proportional to the gas logging values ​​and porosity, and directly proportional to the daily oil and gas equivalent and oil pressure (target layer tubing pressure) of porous reservoirs and low-porosity fractured reservoirs, respectively. Well placement principles: For conventional reservoirs, the reflection coefficient should generally be greater than 0.1, ideally higher than 0.15; for low-porosity fractured reservoirs, areas with well-developed fractures and high production should be sought, with a reflection coefficient between 0.02 and 0.08 being preferable; for inclined oil and gas reservoirs, wells should be placed in the middle or above, not at the bottom.

[0212] Formation pressure can be predicted using reflection coefficients. First, the relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure is established. Then, the reflection coefficient of the target layer in the deployed well is obtained through seismic inversion. By analyzing the relationship between the reflection coefficient and the formation pressure, the formation pressure can be determined.

[0213] Example 2

[0214] Using seismic prediction methods for high-quality reservoirs, an exploration scheme was proposed for the Zhongqiu area. Area 2 is a conventional clastic rock formation with a low exploration success rate, mainly due to the low reflection coefficients of drilled wells, mostly between 0.06 and 0.09, and gas logging values ​​below 30%. Therefore, it is recommended to sidetrack low-yield wells to find strong reflections with a seismic reflection coefficient greater than 0.1, ultimately achieving high production.

[0215] Example 3

[0216] Well locations should be determined based on the quality of the reservoir. A key principle for well placement is: place wells where the reservoir is best, regardless of the structural elevation. Reservoirs with dual-reflection axis characteristics should be prioritized and can be drilled vertically. If a reservoir is inclined, avoid placing wells in the lower parts of the reservoir. Use high-angle wells to drill through more high-quality reservoirs.

[0217] In a certain area, three wells, E and F, have been completed. Figure 9 , 10 These are two appraisal wells. Based on the seismic reflection maps of wells E and F, the Cretaceous strata in well E show weak reflection characteristics, indicating a poor reservoir. The Cretaceous strata in well F show strong reflection characteristics, indicating a better Cretaceous reservoir than well E.

[0218] The reflection coefficients of wells E and F were calculated to be 0.01086 and 0.01505, respectively, with gas logging values ​​of 0.72% and 0.747%. While the gas logging values ​​were similar, the reflection coefficient of well F was 1.38 times that of well E, further demonstrating that the reservoir in well F was superior to that in well E. Test results also confirmed this assessment: well E underwent two fracturing tests with low production, while well F achieved high production after one fracturing test, thus proving the effectiveness of this method in predicting reservoir formation.

[0219] Example 4

[0220] There are two understandings regarding carbonate rock exploration: one is that reservoirs within fracture zones are homogeneous; the other is that they are heterogeneous, mainly concentrated in the beaded center. However, practice has shown that reservoirs within fracture zones are indeed heterogeneous. The two interfaces of the beaded center within a fault-controlled body are high-quality reservoirs, with the most developed reservoirs occurring at the intersection of the inner and outer interfaces and the fracture zone. Further research has revealed that high-quality reservoirs are distributed in the annular zone between the inner and outer interfaces. Therefore, this invention proposes using seismic reflection interfaces to predict high-quality reservoirs within carbonate fault-controlled bodies. This involves establishing relationships between seismic reflection coefficients and physical parameters, gas parameters, oil production parameters, and oil pressure parameters to identify evidence for predicting high-quality reservoirs using seismic reflection interfaces. This provides accurate and effective prediction of fracture-vuggy development zones within novel fault-controlled bodies, timely prediction of overflow and venting zones, timely detection of oil and gas shows, and reference and guidance for optimizing wellbore trajectories.

[0221] In a certain area, 4 positive drilling wells G ( Figure 11 Increase the inclination by 2 degrees, drill the inner boundary of the beaded section, and a good display segment (a1-a2 good display segment) was found. In well H ( Figure 12 The original design targeted point A on the right side of the red bead formation. It was suggested to reduce the inclination and target point C, the lower boundary of the bead formation. However, drilling at point C encountered a cavern, resulting in lost circulation. Drilling over twenty wells has confirmed that carbonate fractured-vuggy reservoirs are mainly distributed at the inner and outer interfaces of the bead formation, with relatively few high-quality reservoirs in the central area.

[0222] This study establishes the relationship between the reflection coefficient of drilled wells and the porosity, gas logging values, daily oil equivalent (unit production) of drilled wells (6mm nozzle), and oil pressure (target formation tubing pressure) of drilled wells (6mm nozzle), exploring the relationship between reflection characteristics and high-quality reservoirs. To calculate the reflection coefficient of drilled wells, wave impedance must be calculated, requiring the use of well logging parameters such as volumetric density. However, many carbonate wells lack volumetric density measurements. Six density curves and parameters were extracted from the seismic maps of key exploration wells in the area. Referring to the volumetric densities measured in wells I and J, and eight other wells in a certain region (five completed wells), the volumetric densities of each well used in the calculation were predicted relatively accurately. The wave impedance of the target formation reservoir section and the wave impedance of the non-reservoir section of the target formation in drilled wells were calculated. The reflection coefficient of the target formation in drilled wells was calculated, and the porosity, gas logging values, daily oil equivalent (6mm nozzle test), and oil pressure (6mm nozzle test) of key wells were statistically analyzed. First, the relationship between the reflection coefficient and the porosity of drilled wells was established. Figure 13 The relationship between the reflection coefficient and the measured values ​​of gas from drilled wells. Figure 14 From these two figures, it can be seen that a reflection coefficient of 0.03-0.1 and a porosity of 2-5.65% indicate fractured reservoirs; a reflection coefficient of 0.1-0.15 and a porosity of 5.65-7.9% indicate fracture-cavitation reservoirs; and a reflection coefficient greater than 0.15 and a porosity greater than 7.9% indicate cavitation reservoirs. Based on this standard, carbonate reservoirs are classified into three categories: fracture-cavitation reservoirs... Figure 13 , 14 Series 3), with caves as the main feature and fractures as a secondary feature, cave-fracture type reservoirs ( Figure 13 , 14 Series 2), with fractures as the main feature and caves as a secondary feature, cave-type reservoirs ( Figure 13 , 14 Series 1) These three types of oil and gas reservoirs are mainly classified based on curve characteristics. To further prove that the reflection coefficient can predict high-quality carbonate reservoirs, a relationship was established between the reflection coefficient and the daily oil production equivalent (6mm nozzle) and oil pressure (6mm nozzle) of the drilled wells. Figure 15 , 16 The reflection coefficient is directly proportional to the daily oil equivalent (6mm nozzle) and oil pressure (6mm nozzle) of the drilled well. As shown in the figure (based only on the collected data): Fractured oil and gas reservoirs: reflection coefficient 0.03-0.1, daily oil equivalent (6mm nozzle) 117-160t, oil pressure (6mm nozzle) 10-42MPa. Fractured-cavity oil and gas reservoirs: reflection coefficient 0.1-0.15, daily oil equivalent (6mm nozzle) 160-270t, oil pressure (6mm nozzle) 28-48MPa. Cavernous oil and gas reservoirs: reflection coefficient greater than 0.15, daily oil equivalent (6mm nozzle) greater than 150t, with the highest actual production reaching 450t, oil pressure (6mm nozzle) greater than 28MPa. Figure 15 , 16This indicates that the reflection coefficient can predict the size of the target oil and gas reservoir and the formation pressure within the depression.

[0223] From the diagram ( Figure 17 The reflection coefficient is directly proportional to the shut-in oil pressure. The shut-in pressure is obtained from the reflection coefficient, and thus the formation pressure is determined. To further determine the formation pressure, a relationship between the reflection coefficient and the formation pressure is established. Figure 18 The above analysis shows that the reflection coefficient can not only predict high-quality carbonate reservoirs, but also predict oil production, oil pressure and formation pressure. The reflection coefficient is a comprehensive reflection of high-quality reservoirs and fluids.

[0224] A carbonate reservoir model was established based on actual drilling and seismic reflection coefficients: A: Carbonate fracture distribution pattern ( Figure 19 B: Distribution pattern of beaded reservoirs in fault-dissolved bodies: These reservoirs are mainly distributed in the upper strata of the beaded network within fault-dissolved bodies. Their seismic reflections exhibit heterogeneous characteristics, characterized by disorder. Figure 20 This model represents the primary exploration target currently. The diagram shows a reservoir prediction at a single point with two surfaces: fractures and vulnerabilities are developed at the inner and outer interfaces, and caverns may develop in the central area. Reservoir configurations are diverse. If a reservoir is likened to a string of beads, this string is divided into a central area and an outer area. The interface of the central area with strong reflection is called the inner interface, and the entire string of beads is the outer interface. High-quality reservoirs are distributed at a single point with two surfaces. The single point represents the reservoir distributed at a specific point in the central area, while the two surfaces represent the reservoirs developed near the inner and outer interfaces. It doesn't simply represent a single surface; all surfaces have a certain thickness. It is important to emphasize that the reservoirs near the intersection of fractures and two surfaces are the most developed, and the zonal high-quality reservoirs between the inner and outer interfaces have been proven in practice.

[0225] Reflection coefficients are used to guide well placement. Since oil and gas are mainly distributed within fractured-vuggy carbonate rocks, carbonate exploration primarily focuses on discovering high-quality fractured-vuggy reservoirs. Well placement principles are: firstly, prioritize cavernous reservoirs with a reflection coefficient greater than 0.15; secondly, prioritize fractured-vuggy reservoirs with a reflection coefficient between 0.03 and 0.15. It should be noted that the reflection coefficients must be obtained from seismic inversion.

[0226] Reflection coefficients obtained through seismic inversion are used to predict formation pressure. The lowest acoustic impedance of the entire bead and the acoustic impedance of the non-reservoir section of the target layer surrounding the bead are calculated from the seismic data volume inversion. The highest reflection coefficient of the bead is then calculated, and its location may indicate the location of a karst cave. Calculations show that the reflection coefficients of the bead in high-pressure wells K and L are both greater than 0.13. Figure 21By comparing this data, it can be determined whether high pressure exists in the deployed well, and corresponding measures can be taken to ensure downhole safety. The optimal reservoir for the beaded formation is the karst cave. From actual drilling experience, the presence of karst cave does not necessarily indicate high pressure, but the presence of high pressure always indicates karst cave. The existence of high pressure must be determined based on the relationship between regional faults and the beaded formation. If there is a large fault near the beaded formation and the reflection coefficient is greater than 0.13, it can be determined that karst cave is developed and normal formation pressure exists because the fault absorbs part of the formation pressure from the beaded formation. If the beaded formation is far from a large regional fault and the reflection coefficient is greater than 0.13, then abnormally high pressure exists in the formation.

[0227] The method provided by this invention can accurately locate carbonate reservoirs, accurately and effectively predict fracture-vuggy development zones within novel fractured solutions, and promptly predict overflow and venting zones, as well as detect oil and gas shows. It also provides reference and guidance for optimizing wellbore trajectories. This method can also predict abnormal high pressure, improving the drilling rate of high-quality reservoirs, ensuring engineering safety, providing technical support for exploration, saving costs, and effectively promoting and improving exploration success rates.

[0228] Example 5

[0229] Using seismic prediction methods for high-quality reservoirs, it is possible to accurately predict wellbore leakage and venting sections in reservoir development, safeguarding engineering safety, allowing for timely adjustments to the wellbore trajectory, and maximizing the encounter with more high-quality reservoirs. For example, well M in a certain area (… Figure 22 The predicted well depth was a3, with a reflection coefficient of 0.03, indicating a possible fractured reservoir and gas detection. In reality, a fracture was encountered at a4, with total hydrocarbons detected at 20%. The difference between well depths a3 and a4 is 15m. The predicted well depth was a5, suggesting a possible wellbore leakage. In reality, a fractured cavity was encountered at a6, resulting in wellbore leakage. The difference between well depths a5 and a6 is 20m. The predicted bottom reflection coefficient was 0.22, indicating a possible cavern at the bottom. A cavern section of 5m length was encountered at a7. Figure 11 , 12 Based on data from points 13 and 16, the well porosity is estimated to be 23%, with gas logging data showing 18% from fractures and 90% from caverns. The daily oil production equivalent is 290t with a 6mm nozzle, and the formation pressure is 97MPa. This allows for the rapid establishment of regional maps and the prediction of high-quality carbonate reservoirs and formation pressure using the reflection coefficient.

[0230] Example 6

[0231] Figure 23 This is a prediction map of high-quality reservoirs in a certain area. Based on the characteristics of the combination of the inner and outer interfaces and fractures, the depth of each interface was predicted. According to actual drilling, well N ( Figure 23The reflection coefficients of the upper interface a8 and a9 were calculated to be 0.07 and 0.21 respectively. Both interfaces showed significant leakage and voiding, particularly at a9, where a 6m void was observed, indicating premature drilling completion with over 100 meters remaining from the target point. The voiding at a9 occurred because it is located at the intersection of the inner interface and a fracture, forming a cavernous reservoir. Figure 11 , 12 Based on data from points 13, 15, and 16, the well porosity is estimated to be 22%, with a maximum gas logging value of 85%. The daily oil production equivalent of the well is 280 tons with a 6mm nozzle, the shut-in oil pressure is 64 MPa, and the formation pressure is 96 MPa.

[0232] Example 7

[0233] The impedance of the beaded wave in a certain well is 13000 g / cm³·m / s, and the impedance of the non-reservoir wave surrounding the beads is 17000 g / cm³·m / s. The calculated reflection coefficient is 0.13. (Based on the attached...) Figure 21 The formation pressure was 149 MPa, indicating that there was abnormally high pressure in the formation. A drilling fluid density of 1.8 was needed to balance the formation pressure. When a drilling fluid density of 1.5 was used, overflow occurred when drilling into the fracture. The drilling fluid density was increased to 1.8, which balanced the formation pressure, and the downhole operation returned to normal.

[0234] Based on the above disclosure, the present invention also provides an electronic device. For example... Figure 24 As shown, the electronic device of this disclosure embodiment includes at least one processor electrically connected to the processor and at least one memory electrically connected to the processor. The memory stores instructions executable by the at least one processor, which, when executed, enables the at least one processor to perform the method steps as described above by the controller. The memory stores a computer program, and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0235] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., computer programs) for executing the above-described prediction model construction method or well location deployment method. This program is capable of accurately predicting high-quality reservoirs and formation pressures, and deploying well locations based on the predicted results. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the prediction model construction method and well location deployment method provided in the above embodiments, and will not be elaborated upon here.

[0236] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the prediction model construction method or well location deployment method described above. The computer program product provided by this application can solve the technical problem that inaccurate prediction of formation pressure in the target layer of the well exploration, especially inaccurate prediction of abnormal high pressure, can easily lead to well blowouts and other accidents. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the prediction model construction method and well location deployment method provided in the above embodiments, and will not be repeated here. Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for constructing a reservoir prediction model based on seismic reflection interface characteristics, characterized in that, The method includes: Based on the seismic data or well logging data of the target work area, obtain the seismic reflection coefficient of the target layer of a single well in the target work area, wherein the seismic reflection coefficient of the target layer of a single well includes the seismic reflection coefficient of the target layer of a drilled well. Based on the seismic reflection coefficient of the target layer in the drilled well, along with well logging data, production data, and well logging data, a reservoir prediction model is constructed.

2. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 1, characterized in that, The logging data includes the highest and second-highest gas measurement values ​​of the target formation that has been drilled; the production capacity data includes the unit production of the drilled well, the tubing pressure of the target formation, and the formation pressure.

3. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 2, characterized in that, Obtain the seismic reflection coefficients of the target layer in the drilled wells of the target work area, including: Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers; Based on the logging data of the target work area, obtain the volume density of the target reservoir section, the propagation velocity of the target reservoir section, the volume density of the target non-reservoir section, and the propagation velocity of the target non-reservoir section; Based on the volumetric density of the target reservoir section, the propagation velocity of the target reservoir section, the volumetric density of the non-reservoir section of the target layer, and the propagation velocity of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer in the target work area is obtained.

4. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 3, characterized in that, Based on the volumetric density of the target reservoir section, the propagation velocity of the target reservoir section, the volumetric density of the target non-reservoir section, and the propagation velocity of the target non-reservoir section, the seismic reflection coefficient of the target well in the target area is obtained, including: Based on the volume density and propagation velocity of the target reservoir segment, the wave impedance of the target reservoir segment is obtained; Based on the volume density and propagation velocity of the non-reservoir section of the target layer, the wave impedance of the non-reservoir section of the target layer is obtained; Based on the wave impedance of the target layer reservoir section and the wave impedance of the target layer non-reservoir section, the seismic reflection coefficient of the target layer in the drilled wells in the target work area is obtained.

5. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 2, characterized in that, Obtaining the seismic reflection coefficients of the target layer in the drilled wells of the target work area also includes: Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers; Based on the seismic data of the target work area, obtain the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer in the drilled well; Based on the wave impedance of the target layer reservoir section and the wave impedance of the target layer non-reservoir section, the seismic reflection coefficient of the target layer in the drilled wells in the target work area is obtained.

6. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 2, characterized in that, Obtaining the seismic reflection coefficients of the target wells in the target work area also includes obtaining the seismic reflection coefficients of the target wells in the carbonate bead region: obtaining seismic profiles based on the seismic data of the target work area; Determine the location of the target layer bead in the drilling based on the seismic profile; Based on the seismic data inversion of the target work area, the lowest wave impedance inside the string of beads and the wave impedance of the non-reservoir section around the string of beads are obtained. Based on the lowest wave impedance inside the beads and the wave impedance of the non-reservoir section around the beads, the seismic reflection coefficient of the drilled target layer in the carbonate rock bead area is obtained.

7. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to any one of claims 2-6, characterized in that, The reservoir prediction model includes: The relationships between the reflection coefficient of the drilled target formation and the porosity of the drilled well, the reflection coefficient of the drilled target formation and the gas measurement value of the drilled well, the reflection coefficient of the drilled target formation and the unit production of the drilled well, the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation, and / or the reflection coefficient of the drilled target formation and the formation pressure of the drilled well.

8. The method for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 7, characterized in that, The relationship between the reflection coefficient of the target formation in a drilled well and the porosity of the drilled well is as follows: y1 = a1x1 + b1 Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or, The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows: y2=a2x2+b2 Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or, The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows: y3 = a3x3 + b3 Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or, The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows: y4 = a4x4 + b4 Where y4 is the reflection coefficient of the drilled target formation related to the tubing pressure of the drilled target formation, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or, The relationship between the reflection coefficient of the target layer in the drilled well and the formation pressure in the drilled well is as follows: y5 = a5x5 + b5 Where y5 is the reflection coefficient of the drilled target layer related to the drilled formation pressure, x5 is the drilled formation pressure, and a5 and b5 are constants.

9. A method for deploying well locations, utilizing a reservoir prediction model constructed according to the methods described in claims 1-8, characterized in that, The method includes: Based on the seismic data of the target work area, the seismic reflection coefficient of the target layer of a single well in the target work area is obtained, and the seismic reflection coefficient of the target layer of the single well includes the seismic reflection coefficient of the target layer of the deployed well. Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted. Under the condition of having a trap, the well location is deployed based on the reservoir development status and formation pressure prediction results of the deployment well.

10. The method according to claim 9, characterized in that, Obtaining the seismic reflection coefficient of the target layer for the well deployment in the target work area also includes: Select the well sections with the highest and second highest gas logging values ​​for each drilled well in the target work area from the logging data, and set the well sections with the highest and second highest gas logging values ​​as the target layers; Based on the seismic data of the target work area, obtain the wave impedance of the target reservoir section and the wave impedance of the non-reservoir section of the target layer of the deployed well; Based on the wave impedance of the reservoir section and the wave impedance of the non-reservoir section of the target layer, the seismic reflection coefficient of the target layer of the well deployed in the target work area is obtained.

11. The method according to claim 9, characterized in that, Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted, including: Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure and / or formation pressure of the target layer of the deployed well are predicted. Based on the highest and second highest gas measurement values ​​corresponding to the target layer of the deployed well, the reservoir development status of the target layer of the deployed well is predicted by porosity and unit production. Based on the target layer tubing pressure and formation pressure corresponding to the target layer of the deployed well, the formation pressure of the target layer of the deployed well is predicted.

12. The method according to claim 9, characterized in that, Well locations are deployed based on reservoir development status and formation pressure prediction results, including: The reservoir development status of the deployed well is a high-quality reservoir, and the well location is as follows; The reservoir development status of the deployed well is poor, so no well site is deployed.

13. The method according to claim 9, characterized in that, When the reservoir development of the deployed well is of high quality, if the predicted formation pressure is higher than the threshold, a drilling fluid that can balance the formation pressure should be selected during the deployment process.

14. A device for constructing a reservoir prediction model based on seismic reflection interface characteristics, characterized in that, The device includes: The first acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target area based on the seismic data or well logging data of the target area. The seismic reflection coefficient of the single well in the target area includes the seismic reflection coefficient of the target layer that has been drilled. The construction unit is used to construct a reservoir prediction model based on the seismic reflection coefficient of the target layer of the drilled well, as well as logging data, production data, and well logging data.

15. The apparatus for constructing a reservoir prediction model based on seismic reflection interface characteristics according to claim 14, characterized in that, The reservoir prediction model includes: The relationships between the reflection coefficient of the drilled target formation and the porosity of the drilled well, the reflection coefficient of the drilled target formation and the gas measurement value of the drilled well, the reflection coefficient of the drilled target formation and the unit production of the drilled well, the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation, and the reflection coefficient of the drilled target formation and the formation pressure are given. The relationship between the reflection coefficient of the target formation in a drilled well and the porosity of the drilled well is as follows: y1 = a1x1 + b1 Where y1 is the reflection coefficient of the target formation in the drilled well, which is related to the porosity of the drilled well, x1 is the porosity of the drilled well, and a1 and b1 are constants; and / or, The relationship between the reflection coefficient of the target formation in a drilled well and the gas measurement value in a drilled well is as follows: y2=a2x2+b2 Where y2 is the reflection coefficient of the target formation in the drilled well related to the drilled gas measurement value, x2 is the drilled gas measurement value, and a2 and b2 are constants; and / or, The relationship between the reflection coefficient of the target formation in a drilled well and the unit production of the drilled well is as follows: y3 = a3x3 + b3 Where y3 is the reflection coefficient of the target layer in the drilled well related to the unit production of the drilled well, x3 is the unit production of the drilled well, and a3 and b3 are constants; and / or, The relationship between the reflection coefficient of the drilled target formation and the tubing pressure of the drilled target formation is as follows: y4 = a4x4 + b4 Where y4 is the reflection coefficient of the drilled target formation related to the unit production of the drilled well, x4 is the tubing pressure of the drilled target formation, a4 and b4 are constants, and / or, The relationship between the reflection coefficient of the target layer in a drilled well and the formation pressure is as follows: y5 = a5x5 + b5 Where y5 is the reflection coefficient of the drilled target layer related to formation pressure, x5 is the formation pressure, and a5 and b5 are constants.

16. An apparatus for deploying well locations, utilizing a reservoir prediction model constructed using the method described in claims 1-8, characterized in that, The device includes: The second acquisition unit is used to acquire the seismic reflection coefficient of a single well in the target work area based on the seismic data of the target work area. The seismic reflection coefficient of a single well in the target layer includes the seismic reflection coefficient of the target layer of the deployment well. The prediction unit is used to predict the reservoir development status and formation pressure of the deployed wells in the target work area based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well. Deployment unit, used to deploy well locations based on reservoir development status and formation pressure prediction results of the deployment well.

17. The apparatus according to claim 16, characterized in that, Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the reservoir development status and formation pressure of the deployed well in the target work area are predicted, including: Based on the reservoir prediction model and the seismic reflection coefficient of the target layer of the deployed well, the highest and second highest gas measurement values, porosity, unit production, target layer tubing pressure and / or formation pressure of the target layer of the deployed well are predicted. Based on the highest and second highest gas measurement values ​​corresponding to the target layer of the deployed well, the reservoir development status of the target layer of the deployed well is predicted by porosity and unit production. Based on the target layer tubing pressure and formation pressure corresponding to the target layer of the deployed well, the formation pressure of the target layer of the deployed well is predicted.

18. The apparatus according to claim 16, characterized in that, Well locations are deployed based on reservoir development status and formation pressure prediction results, including: The reservoir development status of the deployed well is a high-quality reservoir, and the well location is as follows; The reservoir development status of the deployed well is poor, so no well site is deployed.

19. An electronic device comprising at least one processor and at least one memory, the memory being data-connected to the processor, wherein, The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8 or 9-13.

20. A computer-storable medium, characterized in that, The storable medium stores computer instructions, which, when executed by a processor, specifically perform the steps of the method as described in any one of claims 1-8 or 9-13.

21. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they specifically perform the steps of the method as described in any one of claims 1-8 or 9-13.

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