Oil field project evaluation method and device, electronic equipment and storage medium

Abstract

The invention discloses an oil field project evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: for each to-be-applied project of each oil field, acquiring a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions; calling a project evaluation model corresponding to the current to-be-applied project, processing the first prediction data set and the second prediction data set based on the project evaluation model, and determining a benefit increment of the current to-be-applied project; and based on a preset constraint condition and an optimization function corresponding to each optimization target, processing the benefit increments of all the to-be-applied projects, determining a target to-be-applied project corresponding to the target benefit increment, and performing project development based on the target to-be-applied project. According to the technical scheme of the embodiment, the effect of accurately predicting the project benefit is achieved, and the effect of improving the oilfield development benefit on the basis of reducing the oilfield development cost is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and in particular to an oilfield project evaluation method, device, electronic equipment and storage medium. Background Art

[0002] Overseas oil projects are characterized by high risk, large investment, intensive technology and complex contract models. A single well is the smallest unit of oilfield capacity construction, and the management and planning of a single well is the basic guarantee for oilfield capacity construction. Evaluating a single well project is an important means and method to judge the efficiency of drilling operations and the conversion rate of the project.

[0003] In related technologies, the single-well benefit evaluation method of domestic projects is usually used to evaluate overseas oil projects.

[0004] However, the reservoir types, benefit evaluation parameters, oil and gas resource interaction patterns, etc. of overseas projects are not the same. Moreover, a single well is an organic part of the project and cannot be independently evaluated without the project. Therefore, the original single-well benefit evaluation method of domestic projects may lack guidance for the single-well evaluation of overseas projects. As a result, it is impossible to accurately evaluate the benefits of overseas oil projects, affecting the efficiency of oil field development. Summary of the invention

[0005] The present invention provides an oilfield project evaluation method, device, electronic equipment and storage medium to achieve the effect of accurately predicting project benefits, thereby achieving the effect of improving oilfield development benefits while reducing oilfield development costs.

[0006] According to a first aspect of the present invention, there is provided an oilfield project evaluation method, the method comprising:

[0007] For each to-be-applied project of each oil field, a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions are obtained, wherein the different conditions include maintaining the current mining status condition and changing the current mining status condition;

[0008] Retrieving a project evaluation model corresponding to the current project to be applied, and processing the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied;

[0009] Based on the preset constraints and the optimization functions corresponding to the optimization objectives, the benefit increments of all the projects to be applied are processed to determine the identifiers of the projects to be applied corresponding to the target benefit increments;

[0010] Based on the identification of the project to be applied, a target project to be applied is determined, so as to carry out project development based on the target project to be applied.

[0011] According to a second aspect of the present invention, there is provided an oilfield project evaluation device, the device comprising:

[0012] A data set acquisition module is used to acquire, for each to-be-applied project of each oil field, a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions, wherein the different conditions include maintaining the current mining status condition and changing the current mining status condition;

[0013] A benefit increment determination module, configured to retrieve a project evaluation model corresponding to the current project to be applied, and process the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied;

[0014] The benefit increment processing module is used to process the benefit increments of all the projects to be applied based on the preset constraints and the optimization functions corresponding to the optimization objectives, and determine the identifiers of the projects to be applied corresponding to the target benefit increments;

[0015] The project determination module is used to determine a target project to be applied based on the identifier of the project to be applied, so as to carry out project development based on the target project to be applied.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the oilfield project evaluation method described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the oilfield project evaluation method described in any embodiment of the present invention when executed by a processor.

[0021] The technical solution of the embodiment of the present invention obtains the first prediction data set and the second prediction data set corresponding to the current project to be applied under different conditions for each project to be applied in each oil field, and then retrieves the project evaluation model corresponding to the current project to be applied, and processes the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; based on the preset constraint conditions and the optimization function corresponding to each optimization target, the benefit increments of all projects to be applied are processed to determine the identification of the project to be applied corresponding to the target benefit increment; based on the identification of the project to be applied, the target project to be applied is determined, and the project development is carried out based on the target project to be applied, which solves the problem that the original single-well benefit evaluation method of domestic projects in the relevant technology lacks guidance for the single-well evaluation of overseas projects, and then the benefits of overseas oil projects cannot be accurately evaluated, affecting the efficiency of oilfield development, etc., and achieves the effect of accurately predicting the project benefits, and achieves the effect of predicting the project benefits based on different project evaluation models. At the same time, it also achieves the effect of determining the optimization project in the presence of multiple projects, and achieves the effect of improving the oilfield development benefits on the basis of reducing the oilfield development cost.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flow chart of an oilfield project evaluation method provided according to Embodiment 1 of the present invention;

[0025] Figure 2 is a flow chart of an oilfield project evaluation method provided according to Embodiment 2 of the present invention;

[0026] Figure 3 This is a schematic diagram of the structure of an oilfield project evaluation device provided according to Embodiment 3 of the present invention;

[0027] Figure 4 It is a structural schematic diagram of an electronic device for implementing the oilfield project evaluation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment 1

[0031] Figure 1 This is a flow chart of an oilfield project evaluation method provided by the first embodiment of the present invention. This embodiment is applicable to the situation of evaluating and optimizing the benefits of oilfield projects. The method can be executed by an oilfield project evaluation device. The oilfield project evaluation device can be implemented in the form of hardware and / or software. The oilfield project evaluation device can be configured in a terminal and / or a server. Figure 1 As shown, the method includes:

[0032] S110 . For each to-be-applied project in each oil field, obtain a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions.

[0033] Among them, the project to be applied can be understood as an oil field project to be developed and applied. The project to be applied can be any oil and gas development project for the oil field. In this embodiment, the project to be applied can be an overseas oil project. Different conditions can include maintaining the current mining status condition and changing the current mining status condition. Maintaining the current mining status condition can be understood as mining based on the existing oil wells, and can also be understood as mining without drilling new oil wells. On the contrary, changing the current mining status condition can be understood as mining under the condition of drilling at least one new well. The first prediction data set can be understood as a data set obtained by predicting the operating status of the corresponding oil field in the future preset time period under the condition of maintaining the current mining status of the current project to be applied. Correspondingly, the second prediction data set can be understood as a data set after the current project to be applied predicts the operating status of the corresponding oil field in the future preset time period under the condition of changing the current mining status. Optionally, both the first prediction data set and the second prediction data set include oil and gas production prediction data, input resource prediction data, and cost information corresponding to the operation.

[0034] For example, assuming that the current oil field includes 10 existing wells and the preset time period can be one year, the first prediction data set corresponding to the project to be applied in the current oil field under the condition of maintaining the current exploitation status may include the oil and gas production forecast data of the 10 wells in the current oil field in the next year, the resource forecast data invested in the exploitation of the 10 wells, and the cost information corresponding to the exploitation operations performed on the 10 wells; further, assuming that the current oil field is expected to add one well in the next year, it can be determined that the current oil field has changed the current exploitation status. At this time, the second prediction data set corresponding to the project to be applied corresponding to the current oil field under the condition of changing the current exploitation status may include the oil and gas production forecast data of the 11 wells in the current oil field in the next year, the resource forecast data invested in the exploitation of the 11 wells, and the cost information corresponding to the exploitation operations performed on the 11 wells.

[0035] In practical applications, in order to reflect the influence of the three parameters of oil and gas production, input resource value and cost information corresponding to the operation on the project benefit evaluation process, the predetermined oil and gas production prediction interval, input resource value prediction interval and cost information prediction interval corresponding to the operation can be sampled and processed, and then, the first prediction data set and the second prediction data set can be constructed based on the sampled data.

[0036] On the basis of the above technical solutions, it also includes: obtaining a first data set to be processed and a second data set to be processed under different conditions for the current project to be applied; processing the first data set to be processed and the second data set to be processed respectively according to a preset data sampling method to construct a first prediction data set and a second prediction data set corresponding to the current project to be applied.

[0037] Among them, the first data set to be processed can be understood as a data interval data set obtained after the current project to be applied predicts the operating status of the corresponding oil field in the future preset time period under the condition of maintaining the current mining status. Optionally, the first data set to be processed may include a first oil and gas production prediction interval, a first input resource prediction interval, and a cost information prediction interval corresponding to the first operation. Correspondingly, the second data set to be processed can be understood as a data interval data set obtained after the current project to be applied predicts the operating status of the corresponding oil field in the future preset time period under the condition of changing the current mining status. Optionally, the second data set to be processed may include a second oil and gas production prediction interval, a second input resource prediction interval, and a cost information prediction interval corresponding to the second operation. The preset data sampling method may be a predetermined data sampling method. The preset data sampling method may be an arbitrary data sampling method, and optionally, the preset data sampling method may be randomly adopted based on a probability distribution function of corresponding key parameters. Among them, the key parameters may be oil and gas production, input resources, and cost information corresponding to the operation.

[0038] In practical applications, we can first obtain the first data set to be processed corresponding to the current project to be applied under the condition of maintaining the current mining status, and the second data set to be processed corresponding to the current project to be applied under the condition of changing the current mining status. Furthermore, for the data interval corresponding to each key parameter included in the first data set to be processed, we can obtain the probability distribution function corresponding to the current key parameter, and then, we can randomly sample the data interval of the current key parameter according to the probability distribution function to obtain the data set corresponding to the current key parameter. Then, after obtaining the data set corresponding to each key parameter in the first data set to be processed, we can construct the first prediction data set based on each data set. It should be noted that the construction method of the second prediction data set is the same as the construction method of the first prediction data set, and this embodiment will not be described in detail here.

[0039] S120: Retrieve a project evaluation model corresponding to the current project to be applied, and process the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied.

[0040] Among them, the project evaluation model can be understood as a model for determining the predicted benefits of the project. The project evaluation model can be a mathematical model constructed based on a preset logical relationship. The preset logical relationship can match the oil field project. Exemplarily, the preset logical relationship can include a logical relationship determined based on the payment attribute value, a logical relationship determined based on the production sharing ratio, and a logical relationship determined based on the cost information corresponding to the technical service. The benefit increment can be understood as the increased benefit of the expansion project compared with the non-expansion project, that is, the benefits at the same time point under the expansion and non-expansion conditions are subtracted, and the benefit increment is obtained. In this embodiment, the benefit increment can be understood as the increased benefit of the current project to be applied in changing the current mining status conditions and maintaining the current development status conditions. The benefits at the same time point under the two conditions of changing the current mining status conditions and maintaining the current mining status conditions are subtracted, and the benefit increment is obtained.

[0041] In actual applications, for the same oil field, the corresponding project to be applied can be a project built based on different project income and expenditure types, and each project income and expenditure type can correspond to a corresponding project evaluation model. Therefore, when calling the project evaluation model corresponding to the current project to be applied, it can be called according to the project income and expenditure type corresponding to the current project to be applied.

[0042] Optionally, retrieving a project evaluation model corresponding to the current project to be applied includes: determining a project revenue and expenditure type corresponding to the current project to be applied, and retrieving the project evaluation model corresponding to the current project to be applied based on the project revenue and expenditure type.

[0043] The project income expenditure type may be a type that represents the form of project income expenditure. Optionally, the project income expenditure type may include a type corresponding to an expenditure payment attribute value, a type in which output is spent according to a preset ratio, and a type based on cost information corresponding to technical services.

[0044] In practical applications, multiple types of project revenue and expenditure can be determined in advance, and a project evaluation model corresponding to each type of project revenue and expenditure can be constructed. Furthermore, a mapping relationship between the project revenue and expenditure type and the project evaluation model can be established and stored in a database. Furthermore, in the case of determining the current project to be applied, the project revenue and expenditure type can be determined based on the project information included in the current project to be applied, and then the project evaluation model corresponding to the current project to be applied can be determined and retrieved based on the determined project revenue and expenditure type and the mapping relationship between the pre-established project revenue and expenditure type and the project evaluation model.

[0045] Furthermore, after obtaining the project evaluation model corresponding to the current project to be applied, the first prediction data set corresponding to the current project to be applied under the condition of maintaining the current mining status can be input into the acquired project evaluation model, and then the first benefit of the current project to be applied under the condition of maintaining the current mining status can be obtained; further, the second prediction data set corresponding to the current project to be applied under the condition of changing the current mining status can be input into the acquired project evaluation model, and then the second benefit corresponding to the current project to be applied under the condition of changing the current mining status can be obtained. Further, the difference between the second benefit and the second benefit can be determined, and the difference can be used as the benefit increment of the current project to be applied.

[0046] S130 , based on preset constraints and optimization functions corresponding to various optimization objectives, processing the benefit increments of all the projects to be applied, and determining the identifiers of the projects to be applied corresponding to the target benefit increments.

[0047] Among them, the preset constraints can be understood as pre-set conditions that limit the range of variables involved in project optimization. In this embodiment, the preset constraints may include upper and lower limit constraints on oil and gas production, upper limit constraints on input resources, and constraints on whether to change the current mining status. The optimization target can be understood as a predetermined target used when determining the optimal project to be applied among all projects to be applied. In this embodiment, the optimization target may include the maximum net present value, the maximum net present value rate, the maximum preference for the area where the project to be applied is located, and the minimum risk value for the area where the project to be applied is located. Correspondingly, the optimization function can be understood as an objective function corresponding to the optimization target. The identifier of the project to be applied can be identification information for locating the project to be applied. The identifier of the project to be applied can be any form of identification information, and optionally, it can include numbers, letters or other characters.

[0048] In practical applications, after determining the incremental benefits of all projects to be applied, the incremental benefits of all projects to be applied can be processed according to the preset constraints and optimization objectives to evaluate the benefits of all projects to be applied. It should be noted that the optimization objectives set for the benefit evaluation of the projects to be applied include multiple optimization objectives. At this time, the benefit evaluation of the projects to be applied is multi-objective optimization. In order to transform the multi-objective optimization into a single-objective optimization, so as to achieve the effect of minimizing the deviation between the final predicted value and the target value under limited resource conditions, the weights corresponding to each optimization objective can be pre-set according to the project optimization requirements. Then, the target optimization function can be determined according to the optimization function corresponding to each optimization objective and the corresponding weight, so as to evaluate the benefits of all projects to be applied based on the target optimization function and the preset constraints.

[0049] Optionally, the optimization objectives include a first optimization objective, a second optimization objective, a third optimization objective and a fourth optimization objective; accordingly, based on preset constraints and the optimization functions corresponding to each optimization objective, the benefit increments of all projects to be applied are processed to determine the identifier of the project to be applied corresponding to the target benefit increment, including: determining the benefit increment rate corresponding to each project to be applied according to the benefit increment corresponding to each project to be applied, and obtaining the regional preference weight value and the regional risk index value corresponding to each project to be applied; determining the target optimization function according to the optimization function corresponding to the first optimization objective, the optimization function corresponding to the second optimization objective, the optimization function corresponding to the third optimization objective and the optimization function corresponding to the fourth optimization objective; based on the preset constraints and the target optimization function, the benefit increments, benefit increment rates, regional weight values ​​and regional risk index values ​​corresponding to all projects to be applied are processed to determine the identifier of the project to be applied corresponding to the target benefit increment.

[0050] Among them, the first optimization goal can be understood as the goal of optimizing the benefit increment of the application project. The second optimization goal can be understood as the goal of optimizing the benefit increment rate of the application project. The third optimization goal can be understood as the goal of optimizing the preference for the region where the application project is located. The fourth optimization goal can be understood as the goal of optimizing the risk index value of the region where the application project is located. The benefit increment rate can be understood as the ratio between the benefit increment and the input resource value. The benefit increment rate can also be understood as the net present value rate, that is, the ratio between the net present value of the project and the original input resource value of the project. The regional preference weight value can be understood as the value obtained after the regional preference degree is digitized, that is, the regional preference degree is represented by the numerical value. For example, assuming that all the projects to be applied correspond to five areas, namely, area 1, area 2, area 3, area 4 and area 5, the preference levels of these five areas are arranged in order from large to small to obtain area 1, area 3, area 4, area 2 and area 5. Then, according to the arrangement order of the preference levels, a selection can be made from 1-10, and the weight value corresponding to area 1 can be 2, the weight value corresponding to area 3 can be 4, the weight value corresponding to area 3 can be 6, the weight value corresponding to area 2 can be 8, and the weight value corresponding to area 5 can be 10. It should be noted that the regional preference weight value can be customized based on user needs. For different users, after obtaining the same all the projects to be applied, the weight value corresponding to the area where each project to be applied is located may be different.

[0051] Among them, the regional risk index value can be understood as a comprehensive risk index value that characterizes all risks included in the region. It should be noted that the regional preference weight value can be pre-determined and stored in the database for the region where the project to be applied is located. During the project evaluation process, it can be directly retrieved from the database of the region where the project to be applied is located.

[0052] In actual applications, after obtaining the incremental benefits of all projects to be applied, for each project to be applied, the ratio between the incremental benefit corresponding to the current project to be applied and the difference between the second input resource prediction value and the first input resource prediction value can be determined, and then the incremental benefit rate corresponding to the current project to be applied can be obtained. After that, the predetermined regional preference weight value and regional risk index value of the current project to be applied can be obtained.

[0053] Further, the first weight corresponding to the first optimization target, the second weight corresponding to the second optimization target, the third weight corresponding to the third optimization target, and the fourth weight corresponding to the fourth optimization target can be determined, and the first weight is multiplied by the optimization function corresponding to the first optimization target to obtain the first optimization function to be processed, the second weight is multiplied by the optimization function corresponding to the second optimization target to obtain the second optimization function to be processed, the third weight is multiplied by the optimization function corresponding to the third optimization target to obtain the third optimization function to be processed, and the fourth weight is multiplied by the optimization function corresponding to the fourth optimization target to obtain the fourth optimization function to be processed. Furthermore, the first optimization function to be processed, the second optimization function to be processed, the third optimization function to be processed, and the fourth optimization function to be processed can be added together to obtain the target optimization function.

[0054] Furthermore, the benefit increments, benefit increment rates, regional preference weight values ​​and regional risk index values ​​of all projects to be applied can be input into the target optimization function, and the target optimization function can be optimized according to preset constraints to obtain the identification of the project to be applied corresponding to the target benefit increment.

[0055] Exemplarily, the target optimization function can be determined based on the following formula:

[0056] F=a1F1+a2F2+a3F3+a4F4

[0057]

[0058]

[0059]

[0060]

[0061] Wherein, F represents the target optimization function, a1 represents the first weight, F1 represents the optimization function corresponding to the first optimization target, a2 represents the second weight, F2 represents the optimization function corresponding to the second optimization target, a3 represents the third weight, F3 represents the optimization function corresponding to the third optimization target, a4 represents the fourth weight, F4 represents the optimization function corresponding to the fourth optimization target; NPV i represents the benefit increment of the project to be applied, i represents the identifier of the current project to be applied, and x i Indicates whether to change the current mining status, x i It is 0 or 1, 0 means maintaining the current mining status, 1 means changing the current mining status, NPVR i Represents the incremental benefit rate of the project to be applied, PR i Indicates the preference weight value of the project to be applied, RISK i Indicates the risk indicator value of the project to be applied.

[0062] Exemplarily, the preset constraint condition can be determined based on the following formula:

[0063]

[0064]

[0065] Among them, PRO_DOWN represents the lower limit of oil and gas production, PRO_UP represents the upper limit of oil and gas production, and PRO i Indicates the forecast value of oil and gas production of the project to be applied, CAPEX i represents the predicted value of the input resources for the project to be applied, CAPEX_UP represents the upper limit of the input resources, and x i Is 0 or 1.

[0066] S140: Determine a target project to be applied based on the identification of the project to be applied, and perform project development based on the target project to be applied.

[0067] The target application project can be understood as an application project that meets various target optimization objectives and preset constraints. It should be noted that the number of the obtained application project identifiers can be one or more, so the number of the target application projects is also one or more.

[0068] In practical applications, after obtaining the identification of the project to be applied, the project to be applied corresponding to the identification of the project to be applied can be determined according to the association relationship between the project identification and the project established in advance, and the determined project to be applied can be used as the target project to be applied. Furthermore, the corresponding oil field can be developed according to the target project to be applied.

[0069] The technical solution of the embodiment of the present invention obtains the first prediction data set and the second prediction data set corresponding to the current project to be applied under different conditions for each project to be applied in each oil field, and then retrieves the project evaluation model corresponding to the current project to be applied, and processes the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; based on the preset constraint conditions and the optimization function corresponding to each optimization target, the benefit increment of all projects to be applied is processed to determine the identifier of the project to be applied corresponding to the target benefit increment; based on the identifier of the project to be applied, the target project to be applied is determined, and the project development is carried out based on the target project to be applied, which solves the problem that the original domestic project single well benefit evaluation method in the related technology lacks guidance for the single well evaluation of overseas projects, and then the benefits of overseas oil projects cannot be accurately evaluated, affecting the oilfield development efficiency, etc., and achieves the effect of accurately predicting the project benefits, and achieves the effect of predicting the project benefits based on different project evaluation models. At the same time, it also achieves the effect of determining the optimization project in the presence of multiple projects, and achieves the effect of improving the oilfield development benefit on the basis of reducing the oilfield development cost.

[0070] Embodiment 2

[0071] Figure 2 This is a flow chart of an oilfield project evaluation method provided by the second embodiment of the present invention, and based on the above embodiment, S120 is further refined. The technical terms that are the same as or corresponding to the above embodiment are not repeated here.

[0072] like Figure 2 As shown, the method includes:

[0073] S210 . For each to-be-applied project of each oil field, obtain a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions.

[0074] S220: Retrieve a project evaluation model corresponding to the current project to be applied, and process the first prediction data set based on the project evaluation model to obtain a first prediction benefit corresponding to the current project to be applied.

[0075] The first prediction data set includes the first oil and gas production prediction value, the first input resource prediction value and the cost information corresponding to the first operation. The first prediction benefit can be understood as the corresponding project prediction benefit of the current project to be applied under the condition of maintaining the current mining status in the future preset time period.

[0076] In actual applications, after determining the current project to be applied and calling the project evaluation model corresponding to the current project to be applied, the first prediction data set can be processed based on the project evaluation model, and then the first prediction benefit corresponding to the current project to be applied can be obtained.

[0077] In this embodiment, the project evaluation model may include a first evaluation model, a second evaluation model and a third evaluation model. When the project evaluation model corresponding to the current project to be applied is a different evaluation model, the corresponding method for determining the first prediction efficiency also changes accordingly. These project evaluation models may be described in detail below.

[0078] Optionally, when the project evaluation model is the first evaluation model, the first prediction data set is processed based on the project evaluation model to obtain the first predicted benefit corresponding to the current project to be applied, including: when the project evaluation model is the first evaluation model, determining the product between the first oil and gas production prediction value and the first preset ratio to obtain the first payment attribute value, and determining the difference between the first oil and gas production prediction value and the first payment attribute value to obtain the first value to be processed; determining the product between the first value to be processed and the second preset ratio to obtain the first oil and gas recovery value, and determining the difference between the first value to be processed and the first oil and gas recovery value to obtain the second value to be processed; determining the difference between the second value to be processed and the first preset value to obtain the third value to be processed; adding the first oil and gas recovery value and the third value to be processed to obtain the first total recovery value; adding the first input resource prediction value, the cost information corresponding to the first operation, and the second preset value to obtain the first total input value, and determining the difference between the first total recovery value and the first total input value to obtain the first predicted benefit.

[0079] Among them, the first evaluation model can be understood as a model for evaluating project benefits based on the payment attributes of oil and gas projects. The first preset ratio can be understood as a preset ratio of the payment attribute values ​​of oil and gas projects. The first payment attribute value can be understood as the value that needs to be paid to the region under the condition of developing the current project to be applied. The second preset ratio can be understood as the oil and gas profit sharing ratio. The first preset value and the second preset value can be understood as the values ​​corresponding to the different payment attributes of the project to be applied.

[0080] In practical applications, when the project evaluation model is the first evaluation model, the project benefits of the project to be applied can be evaluated from the payment attribute. Specifically, the product between the first oil and gas production forecast value and the first forecast ratio can be determined, and the obtained product can be used as the first payment attribute value. Afterwards, the difference between the first oil and gas production forecast value and the first payment attribute value can be determined, and the obtained difference can be the oil and gas cost value obtained after paying a part of the value of the current project to be applied, and the value can be used as the first value to be processed. Afterwards, the product between the first value to be processed and the second preset ratio can be determined, and the obtained product can be used as the first oil and gas recovery value. Afterwards, the difference between the first value to be processed and the first oil and gas recovery value is determined to obtain the second value to be processed, and the difference between the second value to be processed and the first preset value is determined to obtain the third value to be processed. Further, the first oil and gas recovery value and the third value to be processed can be added to obtain the first total recovery value. Afterwards, the first input resource forecast value, the cost information corresponding to the first operation, and the second preset value can be added to obtain the first total input value. Finally, the difference between the first total recovery value and the first total input value is determined to obtain the first predicted benefit.

[0081] Optionally, the first prediction data set is processed based on the project evaluation model to obtain a first predicted benefit corresponding to the current project to be applied, including: when the project evaluation model is the second evaluation model, determining the product of the first oil and gas production prediction value and the third preset ratio to obtain a second oil and gas recovery value; determining the difference between the first oil and gas production prediction value and the second oil and gas recovery value to obtain a fourth value to be processed; determining the product between the fourth value to be processed and the fourth preset ratio to obtain a fifth value to be processed; adding the second oil and gas recovery value and the fifth value to be processed to obtain a second total recovery value; adding the first input resource prediction value, the cost information corresponding to the first operation, and the third preset value to obtain a second total input value, and determining the difference between the second total recovery value and the second total input value to obtain the first predicted benefit.

[0082] Among them, the second evaluation model can be understood as a model for evaluating project benefits based on the oil and gas production sharing ratio of the oil and gas project. The third preset ratio can be understood as a preset oil and gas cost recovery ratio. The third preset ratio can be associated with the area corresponding to the project to be applied, that is, different oil and gas cost recovery ratios can be corresponding to different areas. The fourth preset ratio can be understood as the oil and gas profit sharing ratio. The third preset value can be a predetermined project payment attribute value.

[0083] In practical applications, when the project evaluation model is the second evaluation model, the project benefits of the project to be applied can be evaluated from the perspective of production sharing. Specifically, the product between the first oil and gas production forecast value and the third forecast ratio can be determined, and the obtained product can be used as the second oil and gas recovery value. Afterwards, the difference between the first oil and gas production forecast value and the second oil and gas recovery value can be determined, and the obtained difference can be the total profit value of the current project to be applied, and the value can be used as the fourth value to be processed. Afterwards, the product between the fourth value to be processed and the fourth preset ratio can be determined, and the obtained product can be the profit value that the owner of the current project to be applied should get, and the value can be used as the fifth value to be processed. Afterwards, the second oil and gas recovery value can be added to the fifth value to be processed to obtain the second total recovery value. Afterwards, the first input resource forecast value, the cost information corresponding to the first operation, and the third preset value can be added to obtain the second total input value. Finally, the difference between the second total recovery value and the second total input value is determined to obtain the first predicted benefit.

[0084] Optionally, when the project evaluation model is the third evaluation model, the first prediction data set is processed based on the project evaluation model to obtain the first predicted benefit corresponding to the current project to be applied, including: when the project evaluation model is the third evaluation model, determining the product of the first oil and gas production prediction value and the fifth preset ratio to obtain a third oil and gas recovery value; determining the difference between the first oil and gas production prediction value and the third oil and gas recovery value to obtain a sixth value to be processed; determining the product between the sixth value to be processed and the sixth preset ratio to obtain a seventh value to be processed; adding the third oil and gas recovery value and the seventh value to be processed to obtain a third total recovery value; adding the first input resource prediction value, the cost information corresponding to the first operation, and the fourth preset value to obtain a third total input value, and determining the difference between the third total recovery value and the third total input value to obtain the first predicted benefit.

[0085] Among them, the third evaluation model can be understood as a model for evaluating project benefits based on the technical service aspects of oil and gas projects. The fifth preset ratio can be understood as a preset oil and gas cost recovery ratio. The fifth preset ratio can be associated with the region corresponding to the project to be applied, that is, different oil and gas cost recovery ratios can correspond to different regions. The sixth preset ratio can be understood as the oil and gas profit sharing ratio. The fourth preset value can be a predetermined project payment attribute value.

[0086] S230: Process the second prediction data set based on the project evaluation model to obtain a second prediction benefit corresponding to the current project to be applied.

[0087] The second prediction data set includes the second oil and gas production prediction value, the second input resource prediction value and the cost information corresponding to the second operation. The second prediction benefit can be understood as the corresponding project prediction benefit of the current project to be applied under the condition of changing the current mining status in the future preset time period.

[0088] In practical applications, the second prediction data set is processed based on the project evaluation model to obtain the second prediction benefit, which is the same as step S220 and will not be described in detail in this embodiment.

[0089] S240: Determine the difference between the second predicted benefit and the first predicted benefit to obtain the benefit increment of the current project to be applied.

[0090] In practical applications, after determining the first predicted benefit and the second predicted benefit of the current project to be applied, the difference between the second predicted benefit and the first predicted benefit can be determined, thereby obtaining the benefit increment of the current project to be applied.

[0091] It should be noted that since the prediction data set is constructed based on data sampling, the prediction data set includes multiple groups of data, each of which may include an oil and gas production forecast value, an input resource forecast value, and cost information corresponding to an operation. Therefore, for the current project to be applied, the number of corresponding benefit increments can match the number of sampled data points. At this time, a probability distribution curve can be determined based on the multiple benefit increments obtained, and then data can be extracted from the probability distribution curve according to a preset data extraction method to obtain the benefit increment corresponding to the current project to be applied. Among them, the preset data extraction method can be a median method.

[0092] S250: Based on preset constraints and optimization functions corresponding to various optimization objectives, the benefit increments of all the projects to be applied are processed to determine the identifiers of the projects to be applied corresponding to the target benefit increments.

[0093] S260: Determine a target project to be applied based on the identification of the project to be applied, and perform project development based on the target project to be applied.

[0094] The technical solution of the embodiment of the present invention obtains the first prediction data set and the second prediction data set corresponding to the current project to be applied under different conditions for each project to be applied in each oil field, and then retrieves the project evaluation model corresponding to the current project to be applied, and processes the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; based on the preset constraint conditions and the optimization function corresponding to each optimization target, the benefit increment of all projects to be applied is processed to determine the identification of the project to be applied corresponding to the target benefit increment; based on the identification of the project to be applied, the target project to be applied is determined, and the project development is carried out based on the target project to be applied, which solves the problem that the original domestic project single well benefit evaluation method in the related technology lacks guidance for the single well evaluation of overseas projects, and then the benefits of overseas oil projects cannot be accurately evaluated, affecting the efficiency of oilfield development, and achieves the effect of accurately predicting the project benefits, and achieves the effect of predicting the project benefits based on different project evaluation models, and at the same time, it also achieves the effect of determining the optimization project in the presence of multiple projects, and achieves the effect of improving the oilfield development benefits on the basis of reducing the oilfield development cost.

[0095] Embodiment 3

[0096] Figure 3 Schematic diagram of the structure of an oilfield project evaluation device provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: a data set acquisition module 310, a benefit increment determination module 320, a benefit increment processing module 330 and a project determination module 340.

[0097] Among them, the data set acquisition module 310 is used to obtain the first prediction data set and the second prediction data set corresponding to the current project to be applied under different conditions for each project to be applied in each oil field, wherein the different conditions include maintaining the current mining status conditions and changing the current mining status conditions; the benefit increment determination module 320 is used to call the project evaluation model corresponding to the current project to be applied, and process the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; the benefit increment processing module 330 is used to process the benefit increments of all projects to be applied based on preset constraints and optimization functions corresponding to each optimization target, and determine the project identifier to be applied corresponding to the target benefit increment; the project determination module 340 is used to determine the target project to be applied based on the project identifier to be applied, so as to carry out project development based on the target project to be applied.

[0098] The technical solution of the embodiment of the present invention obtains the first prediction data set and the second prediction data set corresponding to the current project to be applied under different conditions for each project to be applied in each oil field, and then retrieves the project evaluation model corresponding to the current project to be applied, and processes the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; based on the preset constraint conditions and the optimization function corresponding to each optimization target, the benefit increment of all projects to be applied is processed to determine the identification of the project to be applied corresponding to the target benefit increment; based on the identification of the project to be applied, the target project to be applied is determined, and the project development is carried out based on the target project to be applied, which solves the problem that the original domestic project single well benefit evaluation method in the related technology lacks guidance for the single well evaluation of overseas projects, and then the benefits of overseas oil projects cannot be accurately evaluated, affecting the efficiency of oilfield development, and achieves the effect of accurately predicting the project benefits, and achieves the effect of predicting the project benefits based on different project evaluation models, and at the same time, it also achieves the effect of determining the optimization project in the presence of multiple projects, and achieves the effect of improving the oilfield development benefits on the basis of reducing the oilfield development cost.

[0099] Optionally, the device further includes: a module for acquiring a data set to be processed and a module for sampling a data set.

[0100] A module for acquiring a data set to be processed, used to acquire a first data set to be processed and a second data set to be processed under different conditions for a current application project;

[0101] The data set sampling module is used to process the first data set to be processed and the second data set to be processed respectively according to a preset data sampling method to construct a first prediction data set and a second prediction data set corresponding to the current project to be applied.

[0102] Optionally, the benefit increment determination module 320 includes: a project evaluation model retrieval unit.

[0103] The project evaluation model retrieval unit is used to determine the project income and expenditure type corresponding to the current project to be applied, so as to retrieve the project evaluation model corresponding to the current project to be applied based on the project income and expenditure type.

[0104] Optionally, the benefit increment determination module 320 includes: a first predicted benefit determination unit, a second predicted benefit determination unit and a benefit increment determination unit.

[0105] A first predicted benefit determination unit, configured to process the first predicted data set based on the project evaluation model to obtain a first predicted benefit corresponding to the current project to be applied;

[0106] A second predicted benefit determination unit, configured to process the second predicted data set based on the project evaluation model to obtain a second predicted benefit corresponding to the current project to be applied;

[0107] The benefit increment determination unit is used to determine the difference between the first predicted benefit and the second predicted benefit to obtain the benefit increment corresponding to the current project to be applied.

[0108] Optionally, the project evaluation model includes a first evaluation model, and the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation;

[0109] Correspondingly, the first predicted benefit determination unit includes: a first payment attribute value determination subunit, a first oil and gas recovery value determination subunit, a third to-be-processed value determination subunit, a first total recovery value determination subunit and a first predicted benefit determination subunit.

[0110] A first payment attribute value determination subunit is used to determine the product of the first oil and gas production prediction value and a first preset ratio to obtain a first payment attribute value, and determine the difference between the first oil and gas production prediction value and the first payment attribute value to obtain a first value to be processed when the project evaluation model is the first evaluation model;

[0111] a first oil and gas recovery value determination subunit, configured to determine the product of the first value to be processed and a second preset ratio to obtain a first oil and gas recovery value, and to determine the difference between the first value to be processed and the first oil and gas recovery value to obtain a second value to be processed;

[0112] A third to-be-processed value determination subunit, used to determine the difference between the second to-be-processed value and the first preset value to obtain a third to-be-processed value;

[0113] A first total recovery value determination subunit, configured to add the first oil and gas recovery value and the third to-be-processed value to obtain a first total recovery value;

[0114] The first predicted benefit determination subunit is used to add the first input resource prediction value, the cost information corresponding to the first operation and the second preset value to obtain a first total input value, and determine the difference between the first total recovery value and the first total investment value to obtain the first predicted benefit.

[0115] Optionally, the project evaluation model includes a second evaluation model, the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation,

[0116] Correspondingly, the first predicted benefit determination unit includes: a second oil and gas recovery value determination subunit, a fourth to-be-processed value determination subunit, a fifth to-be-processed value determination subunit, a second total recovery value determination subunit and a first predicted benefit determination subunit.

[0117] A second oil and gas recovery value determination subunit is used to determine the product of the first oil and gas production prediction value and a third preset ratio to obtain a second oil and gas recovery value when the project evaluation model is the second evaluation model;

[0118] a fourth to-be-processed value determination subunit, configured to determine a difference between the first oil and gas production prediction value and the second oil and gas recovery value, to obtain a fourth to-be-processed value;

[0119] a fifth to-be-processed value determination subunit, configured to determine a product between the fourth to-be-processed value and a fourth preset ratio to obtain a fifth to-be-processed value;

[0120] A second total recovery value determination subunit, configured to add the second oil and gas recovery value and the fifth to-be-processed value to obtain a second total recovery value;

[0121] The first predicted benefit determination subunit is used to add the first input resource prediction value, the cost information corresponding to the first operation and the third preset value to obtain a second total input value, and determine the difference between the second total recovery value and the second total investment value to obtain the first predicted benefit.

[0122] Optionally, the project evaluation model includes a third evaluation model, and the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation;

[0123] Accordingly, the first prediction benefit determination unit includes: a third oil and gas recovery value determination subunit, a sixth to-be-processed value determination subunit, a seventh to-be-processed value determination subunit, a third total recovery value determination subunit, and a first prediction benefit determination subunit.

[0124] A third oil and gas recovery value determination subunit is used to determine the product of the first oil and gas production prediction value and a fifth preset ratio to obtain a third oil and gas recovery value when the project evaluation model is the third evaluation model;

[0125] a sixth to-be-processed value determination subunit, configured to determine a difference between the first oil and gas production prediction value and the third oil and gas recovery value, to obtain a sixth to-be-processed value;

[0126] a seventh to-be-processed value determination subunit, configured to determine the product between the sixth to-be-processed value and a sixth preset ratio to obtain a seventh to-be-processed value;

[0127] A third total recovery value determination subunit, configured to add the third oil and gas recovery value to the seventh to-be-processed value to obtain a third total recovery value;

[0128] The first predicted benefit determination subunit is used to add the first input resource prediction value, the cost information corresponding to the first operation and the fourth preset value to obtain a third total input value, and determine the difference between the third total recovery value and the third total investment value to obtain the first predicted benefit.

[0129] Optionally, the optimization target includes a first optimization target, a second optimization target, a third optimization target and a fourth optimization target;

[0130] Correspondingly, the benefit increment processing module 330 includes: a benefit increment rate determination unit, a target optimization function determination unit and a benefit increment processing unit.

[0131] A benefit increment rate determination unit, used to determine the benefit increment rate corresponding to each of the to-be-applied projects according to the benefit increment corresponding to each of the to-be-applied projects, and to obtain a regional weight value and a regional risk index value corresponding to each of the to-be-applied projects;

[0132] a target optimization function determination unit, configured to determine a target optimization function according to the optimization function corresponding to the first optimization target, the optimization function corresponding to the second optimization target, the optimization function corresponding to the third optimization target, and the optimization function corresponding to the fourth optimization target;

[0133] The benefit increment processing unit is used to process the benefit increment, benefit increment rate, regional weight value and regional risk index value corresponding to all the projects to be applied based on the preset constraints and the target optimization function, and determine the identifier of the project to be applied corresponding to the target benefit increment.

[0134] The oilfield project evaluation device provided in the embodiment of the present invention can execute the oilfield project evaluation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0135] Embodiment 4

[0136] Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0137] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0138] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0139] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as an oilfield project evaluation method.

[0140] In some embodiments, the battery charge management method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the oilfield project evaluation method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the oilfield project evaluation method in any other appropriate manner (e.g., by means of firmware).

[0141] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0142] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0143] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0144] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0145] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0146] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0147] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0148] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An oilfield project evaluation method, characterized in that: include: For each to-be-applied project of each oil field, a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions are obtained, wherein the different conditions include maintaining the current mining status condition and changing the current mining status condition; Retrieving a project evaluation model corresponding to the current project to be applied, and processing the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; Based on the preset constraints and the optimization functions corresponding to the optimization objectives, the benefit increments of all the projects to be applied are processed to determine the identifiers of the projects to be applied corresponding to the target benefit increments; Based on the identification of the project to be applied, a target project to be applied is determined, so as to carry out project development based on the target project to be applied.

2. The method according to claim 1, characterized in that: Also includes: Obtaining a first data set to be processed and a second data set to be processed under different conditions for the current application project; The first data set to be processed and the second data set to be processed are processed respectively according to a preset data sampling method to construct a first prediction data set and a second prediction data set corresponding to the current project to be applied.

3. The method according to claim 1, characterized in that: The step of retrieving a project evaluation model corresponding to the current project to be applied includes: Determine the project income and expenditure type corresponding to the current project to be applied, and retrieve the project evaluation model corresponding to the current project to be applied based on the project income and expenditure type.

4. The method according to claim 1, characterized in that: The processing of the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied includes: Processing the first prediction data set based on the project evaluation model to obtain a first prediction benefit corresponding to the current project to be applied; Processing the second prediction data set based on the project evaluation model to obtain a second prediction benefit corresponding to the current project to be applied; The difference between the first predicted benefit and the second predicted benefit is determined to obtain a benefit increment corresponding to the current project to be applied.

5. The method according to claim 1 or 4, characterized in that: The project evaluation model includes a first evaluation model, the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation; Accordingly, the first prediction data set is processed based on the project evaluation model to obtain the first prediction benefit corresponding to the current project to be applied, including: In the case where the project evaluation model is the first evaluation model, determining the product of the first oil and gas production prediction value and the first preset ratio to obtain a first payment attribute value, and determining the difference between the first oil and gas production prediction value and the first payment attribute value to obtain a first value to be processed; Determine the product of the first value to be processed and the second preset ratio to obtain a first oil and gas recovery value, and determine the difference between the first value to be processed and the first oil and gas recovery value to obtain a second value to be processed; Determine the difference between the second value to be processed and the first preset value to obtain a third value to be processed; Adding the first oil and gas recovery value and the third to-be-processed value to obtain a first total recovery value; The first resource input prediction value, the cost information corresponding to the first operation, and the second preset value are added together to obtain a first total input value, and the difference between the first total recovery value and the first total input value is determined to obtain the first predicted benefit.

6. The method according to claim 1 or 4, characterized in that: The project evaluation model includes a second evaluation model, the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation; Accordingly, the first prediction data set is processed based on the project evaluation model to obtain the first prediction benefit corresponding to the current project to be applied, including: In the case where the project evaluation model is the second evaluation model, determining the product of the first oil and gas production prediction value and the third preset ratio to obtain a second oil and gas recovery value; Determine the difference between the first oil and gas production prediction value and the second oil and gas recovery value to obtain a fourth value to be processed; Determine the product of the fourth value to be processed and the fourth preset ratio to obtain a fifth value to be processed; Adding the second oil and gas recovery value and the fifth to-be-processed value to obtain a second total recovery value; The first resource input prediction value, the cost information corresponding to the first operation and the third preset value are added together to obtain a second total input value, and the difference between the second total recovery value and the second total input value is determined to obtain the first predicted benefit.

7. The method according to claim 1 or 4, characterized in that: The project evaluation model includes a third evaluation model, the first prediction data set includes a first oil and gas production prediction value, a first input resource prediction value, and cost information corresponding to a first operation; The processing of the first prediction data set based on the project evaluation model to obtain a first prediction benefit corresponding to the current project to be applied includes: In the case where the project evaluation model is the third evaluation model, determining the product of the first oil and gas production prediction value and the fifth preset ratio to obtain a third oil and gas recovery value; Determine the difference between the first oil and gas production prediction value and the third oil and gas recovery value to obtain a sixth value to be processed; Determine the product of the sixth value to be processed and the sixth preset ratio to obtain a seventh value to be processed; Adding the third oil and gas recovery value to the seventh to-be-processed value to obtain a third total recovery value; The first resource input prediction value, the cost information corresponding to the first operation and the fourth preset value are added together to obtain a third total input value, and the difference between the third total recovery value and the third total input value is determined to obtain the first predicted benefit.

8. The method according to claim 1, characterized in that The optimization objectives include a first optimization objective, a second optimization objective, a third optimization objective and a fourth optimization objective; Accordingly, the benefit increments of all the projects to be applied are processed based on the preset constraints and the optimization functions corresponding to the optimization objectives, and the identifiers of the projects to be applied corresponding to the target benefit increments are determined, including: Determine the benefit increment rate corresponding to each of the projects to be applied according to the benefit increment corresponding to each of the projects to be applied, and obtain the regional weight value and regional risk index value corresponding to each of the projects to be applied; Determine a target optimization function according to the optimization function corresponding to the first optimization objective, the optimization function corresponding to the second optimization objective, the optimization function corresponding to the third optimization objective, and the optimization function corresponding to the fourth optimization objective; Based on the preset constraints and the target optimization function, the benefit increments, benefit increment rates, regional weight values ​​and regional risk index values ​​corresponding to all the projects to be applied are processed to determine the identifiers of the projects to be applied corresponding to the target benefit increments.

9. An oilfield project evaluation device, characterized in that: include: A data set acquisition module is used to acquire, for each to-be-applied project of each oil field, a first prediction data set and a second prediction data set corresponding to the current to-be-applied project under different conditions, wherein the different conditions include maintaining the current mining status condition and changing the current mining status condition; A benefit increment determination module, configured to retrieve a project evaluation model corresponding to the current project to be applied, and process the first prediction data set and the second prediction data set based on the project evaluation model to determine the benefit increment of the current project to be applied; The benefit increment processing module is used to process the benefit increments of all the projects to be applied based on the preset constraints and the optimization functions corresponding to the optimization objectives, and determine the identifiers of the projects to be applied corresponding to the target benefit increments; The project determination module is used to determine a target project to be applied based on the identifier of the project to be applied, so as to carry out project development based on the target project to be applied.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the oilfield project evaluation method according to any one of claims 1 to 8.

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