A method and device for predicting remaining oil under dense well pattern conditions

Abstract

The present invention relates to the technical field of oil reservoir development, and in particular to a method and device for predicting remaining oil under dense well network conditions. The method comprises: acquiring seismic data information, performing secondary frequency enhancement processing on the seismic data information, and obtaining new seismic data information; acquiring geological layer data of the dense well network; obtaining the velocity field of the dense well network based on the new seismic data data, the geological layer data of the dense well network, and the acoustic logging velocity data of some wells; predicting the remaining oil of the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation. When predicting the remaining oil of the dense well network, not only the seismic data information after the frequency enhancement processing is combined, but also the velocity field is combined, and according to the structural interpretation results, the reliability and accuracy of the prediction of the remaining oil of the dense well network are improved, and at the same time, the application degree of the seismic data is also improved.

Description

Technical Field

[0001] The invention relates to the technical field of oil reservoir development, and in particular to a method and a device for predicting remaining oil under dense well network conditions. Background Art

[0002] In the middle and late stages of oilfield development, the density of the well network is relatively high, and compared with the exploration stage, the dense well network has higher requirements for seismic data. As far as the current seismic data is concerned, the prediction of remaining oil in a dense well network is hindered.

[0003] Moreover, the current utilization rate of seismic data is extremely low and cannot meet the needs of well network exploration and development.

[0004] Therefore, how to improve the application of seismic data is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the above problems, the present invention is proposed to provide a method and device for predicting remaining oil under dense well network conditions that overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect, the present invention provides a method for predicting remaining oil under dense well pattern conditions, comprising:

[0007] Obtain earthquake data information;

[0008] Performing secondary frequency enhancement processing on the seismic data information to obtain new seismic data information;

[0009] Acquiring geological stratigraphic data of the dense well network;

[0010] Based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells, the velocity field of the dense well network is obtained;

[0011] Based on the new seismic data information and the velocity field, the remaining oil in the dense well network is predicted on the basis of structural interpretation.

[0012] Furthermore, the obtaining of the velocity field of the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells includes:

[0013] Determine the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells;

[0014] Based on the velocity data of the remaining wells and the acoustic logging velocity data of the partial wells, the velocity field of the dense well network is obtained.

[0015] Further, the determining of the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells includes:

[0016] Determine the time data of the dense well network based on the new seismic data;

[0017] Based on the time data of the dense well network and the geological layer data of the dense well network, and under the constraint of the sonic logging velocity data of the part of the wells, the velocity data of the remaining wells in the dense well network are determined.

[0018] Furthermore, the prediction of the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation includes:

[0019] Based on the new seismic data information and the velocity field, and on the basis of structural interpretation, the drilled wells of the dense well network are predicted to obtain prediction results;

[0020] Comparing the predicted result with the actual result to obtain a predicted matching rate;

[0021] Determining whether the predicted matching rate reaches a preset standard;

[0022] If so, the remaining oil in the dense well network is predicted.

[0023] Furthermore, the prediction of the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation includes:

[0024] Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network.

[0025] Furthermore, based on the new seismic data information and the velocity field, and on the basis of structural interpretation, the remaining oil in the dense well network is predicted by using oil and gas detection technology, including:

[0026] Based on the new seismic data information and the velocity field, faults, fault trains and horizons are interpreted to obtain structural interpretation results;

[0027] Based on the structural interpretation results, oil and gas detection technology is used to predict the remaining oil in the dense well network.

[0028] Furthermore, based on the structural interpretation results, the oil and gas detection technology is used to predict the remaining oil in the dense well network, including:

[0029] Based on the structural interpretation results, oil and gas detection technology is used to determine the remaining oil area of ​​the dense well network when a low-frequency, high-amplitude signal is obtained to obtain a prediction result of the remaining oil in the dense well network.

[0030] Furthermore, after predicting the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation, the method further includes:

[0031] Carry out well location deployment and development adjustments for the remaining oil areas of the determined dense well network.

[0032] In a second aspect, the present invention further provides a device for predicting remaining oil under dense well pattern conditions, comprising:

[0033] A first acquisition module is used to acquire seismic data information;

[0034] A first acquisition module is used to perform a secondary frequency enhancement process on the seismic data information to obtain new seismic data information;

[0035] A second acquisition module is used to acquire geological layer data of the dense well network;

[0036] A second acquisition module is used to obtain the velocity field of the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells;

[0037] The prediction module is used to predict the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation.

[0038] Furthermore, the second obtaining module includes:

[0039] A determination unit, configured to determine the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells;

[0040] The obtaining unit is used to obtain the velocity field of the dense well network based on the velocity data of the remaining wells and the acoustic logging velocity data of the part of the wells.

[0041] Furthermore, the determining unit includes:

[0042] A first determination subunit is used to determine the time data of the dense well network based on the new seismic data;

[0043] The second determination subunit is used to determine the velocity data of the remaining wells in the dense well network based on the time data of the dense well network and the geological layer data of the dense well network, under the constraint of the acoustic logging velocity data of the part of the wells.

[0044] Furthermore, the prediction module includes:

[0045] A first obtaining unit is used to predict the drilled wells of the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation to obtain prediction results;

[0046] A second obtaining unit, used for comparing the predicted result with the actual result to obtain a predicted matching rate;

[0047] A judging unit, used to judge whether the predicted matching rate reaches a preset standard;

[0048] The first prediction unit is used to predict the remaining oil in the dense well network.

[0049] Furthermore, the prediction module is used to:

[0050] Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network.

[0051] In a third aspect, the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method steps when executing the program.

[0052] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above steps when executed by a processor.

[0053] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0054] The present invention provides a method for predicting remaining oil under dense well network conditions, comprising: acquiring seismic data information, performing secondary frequency enhancement processing on the seismic data information, and obtaining new seismic data information; acquiring geological layer data of the dense well network; obtaining the velocity field of the dense well network based on the new seismic data data, the geological layer data of the dense well network, and the acoustic logging velocity data of some wells; predicting the remaining oil of the dense well network based on the new seismic data information and the velocity field on the basis of structural interpretation, and when predicting the remaining oil of the dense well network, not only the seismic data information after the frequency enhancement processing is combined, but also the velocity field is combined, and according to the structural interpretation results, the reliability and accuracy of the prediction of the remaining oil of the dense well network are improved, and at the same time, the application degree of the seismic data is also improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Also, throughout the accompanying drawings, the same reference figures are used to represent the same components. In the drawings:

[0056] Figure 1 A schematic flow chart showing the steps of a method for predicting remaining oil under dense well pattern conditions in an embodiment of the present invention is shown;

[0057] Figure 2 , Figure 3 A schematic diagram showing the comparison of the seismic data before and after the secondary frequency enhancement processing in an embodiment of the present invention is shown;

[0058] Figure 4 A schematic diagram of a velocity field in an embodiment of the present invention is shown;

[0059] Figure 5 , Figure 6 The plan view and cross-sectional view of the new well predicted in the embodiment of the present invention are shown;

[0060] Figure 7 A schematic diagram of a device for predicting remaining oil under dense well pattern conditions in an embodiment of the present invention is shown;

[0061] Figure 8 A schematic diagram of a computer device for implementing a method for predicting remaining oil under dense well pattern conditions in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0062] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0063] Embodiment 1

[0064] The first embodiment of the present invention provides a method for predicting remaining oil under dense well pattern conditions, such as Figure 1 As shown, including:

[0065] S101, obtaining earthquake data information;

[0066] S102, performing secondary frequency enhancement processing on the seismic data information to obtain new seismic data information;

[0067] S103, obtaining geological layer data of dense well network;

[0068] S104, obtaining a velocity field of the dense well network based on new seismic data, geological layer data of the dense well network and acoustic logging velocities of some wells;

[0069] S105, based on new seismic data information and velocity field, on the basis of structural interpretation, predict the remaining oil in the dense well network.

[0070] In a specific application scenario, there are more than 2,000 wells in an oil field, with a well density of 50 to 60 wells / km. 2 , which belongs to a dense well network, with a large north-south structural amplitude and a large velocity difference. Among them, only 20 wells in the southern part of the industry have AC curves, that is, acoustic curves. After 40 years of water injection development, the remaining oil is highly dispersed, and it is necessary to use seismic data for high-resolution reservoir prediction to smoothly predict the distribution of remaining oil in the wells.

[0071] In the above application scenario, how to predict the remaining oil in the dense well network can be achieved through the following solution:

[0072] In a specific implementation, S101, first obtain seismic data information. In the case of sparse well network, the well spacing is large, the occurrence reflected between wells is rough, and the contradiction between well seismic occurrence is not obvious. However, in the case of dense well network, the well spacing is relatively small, and the occurrence depicted between wells is more detailed and accurate, which makes the occurrence of the event axis and the occurrence between wells obviously inconsistent.

[0073] When there is a discrepancy between the occurrence of the event axis in the seismic data and the occurrence of the dense well pattern, the seismic data needs to be processed again.

[0074] Execute S102 to perform secondary frequency enhancement processing on the seismic data information to obtain new seismic data information.

[0075] In a specific implementation method, the seismic data is subjected to a secondary frequency-enhancing process. To address the specific difficulties in seismic interpretation for dense well network development, the seismic data is processed secondary in a targeted and purposeful manner in accordance with development geological needs, so as to change the practice of performing interpretation and processing independently in development seismic.

[0076] Specifically, frequency boosting is to raise the energy of different frequency components of the seismic trace to a consistent level and reconstruct the signal to obtain new seismic data. The resolution of seismic data can be improved by widening the seismic frequency band. Of course, the highest frequency that can be widened by seismic data is related to the seismic acquisition of the original seismic data and cannot be increased indefinitely. If the frequency of seismic data is widened indefinitely, the seismic reflection characteristics of the seismic data will be destroyed. Therefore, an appropriate frequency is required for secondary frequency boosting of seismic data.

[0077] Specific as Figure 2 , Figure 3As shown in the figure, it is a schematic diagram of the seismic data before and after the secondary frequency boosting processing. After the secondary frequency boosting processing, the number of vertical wave groups increases, the occurrence of the event axis is consistent with the occurrence of the dense well network, and it can more truly reflect the occurrence of the formation.

[0078] After obtaining new seismic information, the geological layer data of the dense well network is obtained. Specifically, it is obtained based on the data of the developed wells, which will not be described in detail here.

[0079] Execute S104 to obtain a velocity field of the dense well network based on new seismic data, geological layer data of the dense well network, and acoustic logging velocity data of some wells.

[0080] Since seismic data is in the time domain and geological formation data is in the depth domain, by linking the time domain data with the depth domain data through velocity, we can obtain the velocity data of wells without sonic logging velocity data, thereby constructing the velocity field of a dense well network.

[0081] Specifically, based on new seismic data, geological layer data of the dense well network and acoustic logging velocity data of some wells, velocity data of remaining wells in the dense well network are determined;

[0082] Based on the velocity data of the remaining wells and the acoustic logging velocity data of some wells, the velocity field of the dense well network is obtained.

[0083] Among them, firstly, the time data of the dense well network is determined based on the new seismic data; based on the time data of the dense well network and the geological layer data of the dense well network, under the constraint of the sonic logging speed of some wells, the velocity data of the remaining wells in the dense well network are determined.

[0084] According to the above application scenario, the 20 wells located in the southern part of the work area have acoustic logging velocity data, and the remaining wells in the dense well network have no velocity data. The velocity data of the remaining wells in the dense well network can be obtained based on the geological formation data of the remaining wells, that is, the depth information, and the seismic data data. Specifically, the time data is obtained based on the seismic data data, and the formula of depth data = time data × velocity data is used to obtain the velocity data of the remaining wells in the dense well network.

[0085] Of course, the velocity data is not accurate, and the velocity data of the remaining wells needs to be constrained based on the acoustic logging velocity data of some wells, specifically by correcting them in a differential manner, thereby determining the accurate velocity data of the remaining wells in the dense well network.

[0086] After obtaining the velocity data of the remaining wells in the dense well network, the velocity field of the dense well network is obtained based on the velocity data of the remaining wells and the acoustic logging velocity data of some wells. Figure 4This method overcomes the problem of lack of acoustic wave curves in some wells in the dense well network, and thus changes the practice of using a few calibration wells to control the velocity of the entire dense well network.

[0087] After obtaining a reasonable velocity field of the dense well network, S105 is executed to predict the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation.

[0088] In the process of predicting the remaining oil in the dense well network, the first step is to predict the drilled wells in the dense well network based on the new seismic data information and velocity field and on the basis of structural interpretation to obtain the prediction results.

[0089] Then, the prediction result is compared with the actual result to obtain the prediction matching rate. It is judged whether the prediction matching rate meets the preset standard. For example, the consistency rate of each attribute result of oil and gas prediction reaches 97%.

[0090] When the preset standard is reached, the remaining oil in the local area is predicted.

[0091] In the process of predicting the remaining oil, the oil and gas detection technology is used to predict the remaining oil in the dense well network based on the new seismic data information and velocity field and on the basis of structural interpretation.

[0092] The principle used here is low-frequency resonance and high-frequency attenuation, which can predict highly dispersed oil and gas in the middle and late stages of development.

[0093] Further, based on the new seismic data information and velocity field, faults, fractures and horizons are interpreted to obtain structural interpretation results;

[0094] Based on the structural interpretation results, oil and gas detection technology is used to predict the remaining oil in the dense well network.

[0095] Among them, based on the structural interpretation results, oil and gas detection technology is used to determine the remaining oil area of ​​the dense well network when a low-frequency, high-amplitude signal is obtained to obtain the prediction result of the remaining oil in the dense well network.

[0096] By predicting the area of ​​favorable sand bodies, the remaining oil in the dense well network can be obtained. Specifically, based on the seismic data information and velocity field, a target layer is obtained through the structural interpretation results, and prediction is performed for the target layer.

[0097] For the target layer, oil and gas detection technology is used to predict the remaining oil. In the oil and gas detection technology, by emitting sound waves, a reflected signal is obtained, and then the lithology of the layer is determined based on the frequency information and amplitude information in the reflected signal. In the present invention, when the frequency information and amplitude information are low-frequency and high-amplitude signals, it is determined that there is a favorable sand body in the area, and the area is determined as a remaining oil area, thereby obtaining the prediction result of the remaining oil in the dense well network.

[0098] After predicting the remaining oil in the dense well network, it also includes: adjusting the well location and development of the remaining oil in the determined dense well network.

[0099] Well site deployment and development adjustments are carried out for the predicted wells. Specifically, the well site deployment is carried out based on the single well oil test, test production data and oil control factor analysis results.

[0100] like Figure 5 Floor plan, Figure 6 The cross-section shown shows that favorable sand bodies are predicted to develop in the Well-A to Well-B strip on the edge. Therefore, the location of the new well is predicted between Well-A and Well-B.

[0101] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0102] The present invention provides a method for predicting remaining oil under dense well network conditions, comprising: acquiring seismic data information, performing secondary frequency enhancement processing on the seismic data information, and obtaining new seismic data information; acquiring geological layer data of the dense well network; obtaining the velocity field of the dense well network based on the new seismic data data, the geological layer data of the dense well network, and the acoustic logging velocity data of some wells; predicting the remaining oil of the dense well network based on the new seismic data information and the velocity field on the basis of structural interpretation, and when predicting the remaining oil of the dense well network, not only the seismic data information after the frequency enhancement processing is combined, but also the velocity field is combined, and according to the structural interpretation results, the reliability and accuracy of the prediction of the remaining oil of the dense well network are improved, and at the same time, the application degree of the seismic data is also improved.

[0103] Embodiment 2

[0104] Based on the same inventive concept, the present invention also provides a device for predicting remaining oil under dense well pattern conditions, such as Figure 7 As shown, including:

[0105] The first acquisition module 701 is used to acquire seismic data information;

[0106] The first acquisition module 702 is used to perform a secondary frequency enhancement process on the seismic data information to obtain new seismic data information;

[0107] The second acquisition module 703 is used to acquire the geological layer data of the dense well network;

[0108] A second acquisition module 704 is used to obtain the velocity field of the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells;

[0109] The prediction module 705 is used to predict the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation.

[0110] In an optional implementation, the first obtaining module 702 includes:

[0111] A determination unit, configured to determine the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells;

[0112] The obtaining unit is used to obtain the velocity field of the dense well network based on the velocity data of the remaining wells and the acoustic logging velocity data of the part of the wells.

[0113] In an optional implementation, the determining unit includes:

[0114] A first determination subunit is used to determine the time data of the dense well network based on the new seismic data;

[0115] The second determination subunit is used to determine the velocity data of the remaining wells in the dense well network based on the time data of the dense well network and the geological layer data of the dense well network, under the constraint of the acoustic logging velocity data of the part of the wells.

[0116] In an optional implementation, the prediction module 705 includes:

[0117] A first obtaining unit is used to predict the drilled wells of the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation to obtain prediction results;

[0118] A second obtaining unit, used for comparing the predicted result with the actual result to obtain a predicted matching rate;

[0119] A judging unit, used to judge whether the predicted matching rate reaches a preset standard;

[0120] The first prediction unit is used to predict the remaining oil in the dense well network.

[0121] In an optional implementation, the prediction module 705 is used to:

[0122] Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network.

[0123] In an optional implementation, the prediction module 705 includes:

[0124] A third obtaining unit is used to interpret faults, fault series and horizons based on the new seismic data information and the velocity field to obtain a structural interpretation result;

[0125] The second prediction unit is used to predict the remaining oil in the dense well network based on the structural interpretation result and using oil and gas detection technology.

[0126] In an optional implementation manner, the second prediction unit is configured to:

[0127] Based on the structural interpretation results, oil and gas detection technology is used to determine the remaining oil area of ​​the dense well network when a low-frequency, high-amplitude signal is obtained to obtain a prediction result of the remaining oil in the dense well network.

[0128] In an optional implementation, the method further includes: deploying a module:

[0129] Carry out well location deployment and development adjustments for the remaining oil areas of the determined dense well network.

[0130] Embodiment 3

[0131] Based on the same inventive concept, an embodiment of the present invention provides a computer device, such as Figure 8 As shown, it includes a memory 804, a processor 802, and a computer program stored in the memory 804 and executable on the processor 802. When the processor 802 executes the program, the steps of the method for predicting remaining oil under dense well network conditions are implemented.

[0132] Among them, Figure 8 In the embodiment of the present invention, a bus architecture (represented by bus 800) is shown, which may include any number of interconnected buses and bridges, and bus 800 links various circuits including one or more processors represented by processor 802 and memory represented by memory 804. Bus 800 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 806 provides an interface between bus 800 and receiver 801 and transmitter 803. Receiver 801 and transmitter 803 may be the same element, namely a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 802 is responsible for managing bus 800 and general processing, while memory 804 may be used to store data used by processor 802 when performing operations.

[0133] Embodiment 4

[0134] Based on the same inventive concept, a fourth embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for predicting remaining oil under dense well pattern conditions.

[0135] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0136] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0137] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the intention that the claimed invention requires more features than those explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present invention.

[0138] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0139] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0140] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components of a device for predicting residual oil under dense well network conditions according to an embodiment of the present invention, a computer device. The present invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0141] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc., does not indicate any order. These words may be interpreted as names.

Claims

1. A method for predicting remaining oil under dense well pattern conditions, characterized in that: include: Obtain earthquake data information; Performing secondary frequency enhancement processing on the seismic data information to obtain new seismic data information; Acquiring geological stratigraphic data of the dense well network; Based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells, the velocity field of the dense well network is obtained; Based on the new seismic data information and the velocity field, on the basis of structural interpretation, predict the remaining oil in the dense well network; The frequency boosting process is to raise the energy of different frequency components of the seismic trace to a consistent level, and perform signal reconstruction to obtain new seismic data, so that the occurrence of the event axis is consistent with the occurrence of the dense well pattern; The method of obtaining the velocity field of the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells comprises: Determine the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells; Based on the velocity data of the remaining wells and the acoustic logging velocity data of the partial wells, the velocity field of the dense well network is obtained.

2. The method according to claim 1, characterized in that Determining the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells includes: Determine the time data of the dense well network based on the new seismic data; Based on the time data of the dense well network and the geological layer data of the dense well network, and under the constraint of the sonic logging velocity data of the part of the wells, the velocity data of the remaining wells in the dense well network are determined.

3. The method according to claim 1, characterized in that The method of predicting the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation includes: Based on the new seismic data information and the velocity field, and on the basis of structural interpretation, the drilled wells of the dense well network are predicted to obtain prediction results; Comparing the predicted result with the actual result to obtain a predicted matching rate; Determining whether the predicted matching rate reaches a preset standard; If so, the remaining oil in the dense well network is predicted.

4. The method according to claim 1, characterized in that The method of predicting the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation includes: Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network.

5. The method according to claim 4, characterized in that Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network, including: Based on the new seismic data information and the velocity field, faults, fault trains and horizons are interpreted to obtain structural interpretation results; Based on the structural interpretation results, oil and gas detection technology is used to predict the remaining oil in the dense well network.

6. The method according to claim 5, characterized in that Based on the structural interpretation results, the remaining oil in the dense well network is predicted by using oil and gas detection technology, including: Based on the structural interpretation results, oil and gas detection technology is used to determine the remaining oil area of ​​the dense well network when a low-frequency, high-amplitude signal is obtained to obtain a prediction result of the remaining oil in the dense well network.

7. The method according to claim 6, characterized in that After predicting the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation, the method further includes: Carry out well location deployment and development adjustments for the remaining oil areas of the determined dense well network.

8. A device for predicting remaining oil under dense well pattern conditions, characterized in that: include: A first acquisition module is used to acquire seismic data information; A first acquisition module is used to perform a secondary frequency enhancement process on the seismic data information to obtain new seismic data information; A second acquisition module is used to acquire geological layer data of the dense well network; A second acquisition module is used to obtain the velocity field of the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells; A prediction module, for predicting the remaining oil in the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation; The frequency boosting process is to raise the energy of different frequency components of the seismic trace to a consistent level, and perform signal reconstruction to obtain new seismic data, so that the occurrence of the event axis is consistent with the occurrence of the dense well pattern; The second acquisition module comprises: A determination unit, configured to determine the velocity data of the remaining wells in the dense well network based on the new seismic data, the geological layer data of the dense well network and the acoustic logging velocity data of some wells; An obtaining unit is used to obtain the velocity field of the dense well network based on the velocity data of the remaining wells and the acoustic logging velocity data of the part of the wells.

9. The device according to claim 8, characterized in that The determining unit comprises: A first determination subunit is used to determine the time data of the dense well network based on the new seismic data; The second determination subunit is used to determine the velocity data of the remaining wells in the dense well network based on the time data of the dense well network and the geological layer data of the dense well network, under the constraint of the acoustic logging velocity data of the part of the wells.

10. The device according to claim 8, characterized in that The prediction module comprises: A first obtaining unit is used to predict the drilled wells of the dense well network based on the new seismic data information and the velocity field and on the basis of structural interpretation to obtain prediction results; A second obtaining unit, used for comparing the predicted result with the actual result to obtain a predicted matching rate; A judging unit, used to judge whether the predicted matching rate reaches a preset standard; The first prediction unit is used to predict the remaining oil in the dense well network.

11. The device according to claim 8, characterized in that The prediction module is used to: Based on the new seismic data information and the velocity field, on the basis of structural interpretation, oil and gas detection technology is used to predict the remaining oil in the dense well network.

12. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method steps according to any one of claims 1 to 7 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method steps as claimed in any one of claims 1 to 7 are implemented.

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