A method and device for predicting the productivity of a carbonate fractured-vuggy reservoir

Abstract

The application provides a carbonate fracture-cave type reservoir productivity prediction method and device. The method comprises the following steps: obtaining logging data and seismic data of a to-be-tested reservoir; obtaining a beaded shape of the to-be-tested reservoir according to the logging data and the seismic data, wherein the beaded shape is used to indicate a protruding direction of a contour of a beaded pearl; and predicting the productivity of the to-be-tested reservoir according to a pre-obtained corresponding relationship between the productivity of the reservoir and the beaded shape. In this way, the method can predict how much the productivity of the to-be-tested reservoir is in advance, and the efficiency of drilling out oil and gas is improved.

Description

Technical Field

[0001] This application relates to the field of petroleum technology, and in particular to a method and apparatus for predicting the production capacity of carbonate rock fracture-vuggy reservoirs. Background Technology

[0002] In the petroleum industry, carbonate fracture-vuggy reservoirs can be composed of three types of reservoir structures: fracture structure, pore structure, or cave structure. In many regions, carbonate fracture-vuggy oil reservoirs provide important locations for the accumulation and transportation of oil and natural gas.

[0003] In existing technologies, the differences in the strength and shape of seismic reflections from strata are mainly used to simply distinguish whether a reservoir is filled with oil and gas, and the strength of the beaded reflections can only reflect whether the reservoir is clearly visible.

[0004] However, since there is no clear correlation between the size of the production capacity and the strength of the bead reflection, this method cannot predict the size of the reservoir's oil and gas production capacity. Summary of the Invention

[0005] This application provides a method and apparatus for predicting the production capacity of carbonate rock fractured-vuggy reservoirs, which solves the problem that existing technologies cannot predict the size of oil and gas production capacity of reservoirs.

[0006] In a first aspect, embodiments of this application provide a method for predicting the production capacity of a carbonate fracture-vuggy reservoir, comprising: acquiring well logging data and seismic data of the reservoir to be tested; obtaining a beaded morphology of the reservoir to be tested based on the well logging data and the seismic data, wherein the beaded morphology is used to indicate the protruding direction of the outline of the beads; and predicting the production capacity of the reservoir to be tested based on a pre-obtained correspondence between the reservoir production capacity and the beaded morphology.

[0007] In one possible implementation, obtaining the beaded morphology of the reservoir to be tested based on the well logging data and the seismic data includes: determining the outline of the beaded morphology of the reservoir to be tested based on the well logging data and the seismic data; and obtaining the beaded morphology of the reservoir to be tested based on the curvature corresponding to the outline.

[0008] In one possible implementation, the bead pattern includes at least one of the following: a downward-floating state, an upward-protruding state, or an indistinct state; based on a pre-obtained correspondence between reservoir capacity and bead pattern, the capacity of the reservoir to be tested is predicted, including at least one of the following: if the bead pattern corresponding to the reservoir is a downward-floating state, then the capacity of the reservoir corresponding to the reservoir is predicted to be a high-efficiency well, and the capacity of the high-efficiency well is greater than a first threshold; if the bead pattern corresponding to the reservoir is an upward-protruding state, then the capacity of the reservoir corresponding to the reservoir is predicted to be a medium-efficiency well, and the capacity of the medium-efficiency well is greater than a second threshold, wherein the first threshold is greater than the second threshold; if the bead pattern corresponding to the reservoir is an indistinct state, then the capacity of the reservoir corresponding to the reservoir is predicted to be an inefficient well, and the capacity of the inefficient well is less than the second threshold.

[0009] In one possible implementation, the first threshold is 20,000 tons and the second threshold is 2,000 tons.

[0010] In one possible implementation, the method for predicting the production capacity of carbonate fracture-vuggy reservoirs may further include: acquiring well logging data and seismic data of multiple reservoirs within a block; obtaining the beaded pattern of the multiple reservoirs based on the well logging data and the seismic data; establishing a correspondence between the production capacity of the reservoirs and the beaded pattern based on the beaded pattern and the cumulative production information corresponding to the multiple reservoirs; wherein the correspondence is used to predict the production capacity of the reservoirs to be tested within the block.

[0011] In one possible implementation, the logging data includes at least one of the following: single well coordinates, wellbore depth, well inclination angle, logging information, lithological composition, and stratification status; determining the outline of the beaded structure of the reservoir under test based on the logging data and the seismic data includes: acquiring the logging data and the seismic data, and analyzing the outline of the beaded structure of the reservoir based on landmark software.

[0012] Secondly, embodiments of this application provide a device for evaluating the productivity of a carbonate fracture-vuggy reservoir, comprising: an acquisition module for acquiring well logging data and seismic data of the reservoir to be tested; a processing module for obtaining a beaded morphology of the reservoir to be tested based on the well logging data and the seismic data, wherein the beaded morphology indicates the protruding direction of the beaded outline; and a prediction module for predicting the productivity of the reservoir to be tested based on a pre-obtained correspondence between the reservoir productivity and the beaded morphology.

[0013] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, and a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor, and the computer program includes instructions for performing the carbonate fracture-vuggy reservoir productivity prediction method as described in any of the first aspects.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the carbonate rock fracture-vuggy reservoir production prediction method as described in any of the first aspects.

[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the carbonate rock fracture-vuggy reservoir capacity prediction method as described in any one of the first aspects.

[0016] In summary, the embodiments of this application can obtain the beaded pattern of the reservoir based on the obtained well logging data and seismic data of the reservoir to be tested, and further predict the production capacity of the reservoir to be tested based on the pre-obtained correspondence between the reservoir production capacity and the beaded pattern. This can provide an effective and reliable production capacity prediction method for drilling, and improve the efficiency of drilling out oil and gas. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0018] Figure 2 A flowchart illustrating a method for predicting the production capacity of a carbonate rock fracture-vuggy reservoir, provided as an embodiment of this application;

[0019] Figure 3A A schematic diagram of a geological model of the downward drift state provided in an embodiment of this application;

[0020] Figure 3B This is a technical schematic diagram illustrating the eyeball effect that occurs when the bottom boundary of a low-velocity geological body is pulled down, as provided in an embodiment of this application.

[0021] Figure 4A A schematic diagram of a geological model of the upward protrusion state provided in this application embodiment;

[0022] Figure 4B A schematic diagram illustrating the technical principle of raising the eyeball effect on the bottom boundary of a high-speed geological body, provided in this application embodiment;

[0023] Figure 5 A schematic diagram illustrating the process of obtaining the beaded shape of the reservoir to be tested, provided for an embodiment of this application;

[0024] Figure 6 A schematic cross-sectional view of an efficient well provided in an embodiment of this application;

[0025] Figure 7 A cross-sectional schematic diagram of a medium-efficiency well provided in an embodiment of this application;

[0026] Figure 8 A schematic cross-sectional view of an inefficient well provided in an embodiment of this application;

[0027] Figure 9 A flowchart illustrating the correspondence between the production capacity of multiple storage tanks and their bead-like configuration, provided as an embodiment of this application;

[0028] Figure 10 A schematic diagram of the structure of the carbonate rock fissure-vuggy reservoir capacity prediction device provided in the embodiments of this application;

[0029] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0030] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and purpose. For example, "first device" and "second device" are merely used to distinguish different devices and do not limit their order of execution. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0031] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0032] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0033] The embodiments of this application are described below with reference to the accompanying drawings. The method for predicting the productivity of carbonate fractured-vuggy reservoirs provided in this application can be applied to, for example... Figure 1 In the application scenarios shown.

[0034] Figure 1 An application scenario diagram provided for an embodiment of this application, such as... Figure 1 As shown, carbonate rock fracture-cavity reservoirs are diverse in type and size, and can include reservoirs of various sizes such as reservoir 1, reservoir 2, reservoir 3, reservoir 4, reservoir 5, and reservoir 6. These reservoirs 1-6 can store different substances such as oil, gas, and water.

[0035] One possible implementation is to distinguish reservoirs by utilizing the differences in the strength and shape of seismic reflections from the formation, and to determine whether the reservoir is filled with oil and gas. Based on the strength of the seismic reflections, the beaded reflection type can be further subdivided into "strong" beaded reflections and "weak" beaded reflections. If the seismic reflection strength of a certain reservoir is of the "strong" beaded reflection type, it means that the reservoir is filled with oil and gas. If the seismic reflection strength of a certain reservoir is of the "weak" beaded reflection type, it means that the reservoir is not filled with oil and gas.

[0036] However, classifying the seismic reflection intensity of a reservoir into beaded reflection types can only determine whether the reservoir is filled with oil and gas, but cannot predict the size of the reservoir's oil and gas production capacity, and there is no obvious correlation between the size of the production capacity and the strength of the beaded reflection.

[0037] Therefore, this application provides a method for predicting the production capacity of carbonate fractured-vuggy reservoirs. This method can obtain the beaded pattern of the reservoir based on the well logging data and seismic data of the reservoir to be tested, and further predict the production capacity of the reservoir based on the pre-obtained correspondence between the reservoir production capacity and the beaded pattern. This method can provide an effective and reliable prediction method for drilling and improve the success rate of drilling out oil and gas.

[0038] For example, Figure 2 A flowchart illustrating a method for predicting the production capacity of carbonate fractured-vuggy reservoirs provided in this application is shown below. Figure 2 As shown, the method in this application embodiment includes:

[0039] S201. Obtain well logging data and seismic data of the reservoir to be measured.

[0040] In this embodiment of the application, the reservoir to be measured can refer to the pores and fractures of the oil and gas storage space to be measured, and the logging data can refer to different parameter data related to the reservoir, including: single well coordinates, wellbore depth, well inclination angle, logging information, lithological composition, stratification status and other parameter data.

[0041] Among them, the coordinates of a single well are the wellhead coordinates of a reservoir well, which can refer to the coordinates of the center position of the oil drilling rig rotary table, and have three coordinate elements: longitude, latitude, and altitude. For example, the coordinates of a certain single well can be (56°30'00.70"N, 99°07'34.45"W, 50).

[0042] Wellbore depth can be divided into vertical shaft depth and inclined shaft depth. This depth refers to the total length of the well neck, shaft, and bottom. The section of the wellbore closest to the surface is called the well neck, and various orifices are often located in this section. The shaft is the main part of the wellbore and accounts for the largest proportion of the well depth. The bottom depth is determined by the hoisting overwind height, the requirements of the bottom equipment, and the depth of the bottom water pocket. The overwind height refers to the safety distance left when determining the derrick height to avoid potential collision damage to the container on the derrick during overwinding. For example, the wellbore depth of a certain storage tank might be 90 meters.

[0043] Well inclination angle refers to the angle between the central axis of a point in an oil or water well and the vertical line of the earth. Its range is 0° to 180°. This well inclination angle can be used to indicate the inclination of the wellbore trajectory. For example, the well inclination angle of a reservoir can be 15°.

[0044] Well logging information refers to the physical parameters generated by a logging machine when measuring a well, such as resistivity, spontaneous potential, sonic velocity, and rock bulk density. For example, a well might generate data showing a resistivity of 1, a spontaneous potential of 2, a sonic velocity of 3, and a rock bulk density of 5.

[0045] Lithological composition can refer to some properties of a rock, such as its color, composition, structure, cement, cementation type, and special minerals. For example, if the rock is dacite, it is characterized by its light color, usually gray or grayish-white, porphyritic texture, and the phenocrysts are mostly intermediate plagioclase, with less alkali plagioclase, and may sometimes contain a small amount of quartz.

[0046] Stratification refers to the various stratified and non-stratified rock states formed during the development of the Earth's crust. Geological stratification can be carried out through several aspects, including chronological stratification, lithological stratification, and sequence stratigraphy. Chronological stratification is determined by isotopic dating and paleontological fossil assemblage dating. Lithological stratification is based on different lithological assemblages of different ages to determine the boundaries of strata. Sequence stratigraphy is based on global relative sea-level rise and fall curves to classify strata. For example, based on lithological stratification, strata can be divided into sedimentary strata, igneous strata, and metamorphic strata.

[0047] It should be noted that the embodiments of this application do not specifically limit the values ​​of single well coordinates, wellbore depth, well inclination angle, resistivity, spontaneous potential, sonic velocity, and rock bulk density. The values ​​in the embodiments of this application are only illustrative examples.

[0048] In this embodiment of the application, seismic data may refer to seismic signal frequency domain data collected and recorded by seismic exploration instruments, which includes oil and gas information.

[0049] For example, in Figure 1 In the application scenario, if the reservoir to be measured is reservoir 1, it is necessary to obtain the seismic data and well logging data of reservoir 1, that is, the single well coordinates, wellbore depth, well inclination angle, well logging information, lithological composition, and stratification status of reservoir 1. For example, the obtained single well coordinates of reservoir 1 are (56°30'00.70"N, 99°07'34.45"W, 50); the wellbore depth is 90 meters; the well inclination angle is 15°; the well logging information is that the resistivity is 1, the spontaneous potential is 2, the sonic velocity is 3, the rock bulk density is 5; the lithological composition is dacite; and the stratification status is sedimentary rock.

[0050] S202. Based on well logging data and seismic data, the bead pattern of the reservoir to be measured is obtained. The bead pattern is used to indicate the protruding direction of the bead outline.

[0051] In this embodiment of the application, the bead pattern can refer to the different states into which the reservoir is divided based on the different principles of seismic wave reflection in rocks and fluids, using the "eyeball effect". These states can include three types: downward floating state, upward protruding state, and indistinct state, which can be used to indicate the protruding direction of the bead's outline.

[0052] The "eyeball effect" refers to the different phenomena that occur when seismic reflected waves travel at different speeds in the strata and fluids.

[0053] The term "downward drift" refers to the phenomenon where, after a seismic reflected wave passes through a low-velocity layer, its propagation speed decreases, its travel time becomes relatively longer, and a "downward drift" occurs beneath the low-velocity geological body. Specifically, for example... Figures 3A-3B As shown, Figure 3A This is a schematic diagram of a geological model of the downward drift state provided in an embodiment of this application. Figure 3B The technical principle diagram for the "eyeball effect" appearing when the bottom boundary of a low-velocity geological body is pulled down, as provided in the embodiments of this application, should be noted as follows: Figure 3B for Figure 3A The diagram shows the technical principle behind the eyeball effect corresponding to the geological model shown.

[0054] For example, Figure 3A The horizontal axis is the X-axis, which represents the horizontal plane of the Earth's surface. The vertical axis is the H-axis, which represents the depth of the geological layers. The numbers 1-5 represent geological layers at different depths. The horizontal lines are the boundaries between different geological layers, which can represent the bottom boundaries of geological layers 1-4. These geological layers 1-5 correspond to the propagation speeds of V1-V5, respectively. Among them, the propagation speeds of V1, V2, and V5 are similar, the propagation speed of V3 is greater than that of V2, and the propagation speed of V4 is less than that of V2.

[0055] Figure 3B The horizontal axis is the X-axis, which also represents the Earth's surface level. The vertical axis is the t-axis, which represents the travel time of seismic reflected waves through the geological layers. The numbers 1-5 represent the meanings of... Figure 3A The same applies here, so I will not repeat it again. The horizontal line is the boundary line between geological layer 1, geological layer 2 and geological layer 3, and the curve is the boundary line between geological layer 3, geological layer 4 and geological layer 5. The above boundary lines can represent the bottom boundary of the geological body of geological layers 1-4. Because the propagation speed of seismic reflected waves decreases after passing through geological layer 4, the travel time becomes relatively longer. The boundary line between geological layer 4 and geological layer 5 shows a downward pull phenomenon. Therefore, this downward pull phenomenon is the eyeball effect of the downward drift state.

[0056] The "upward protrusion" state can refer to the phenomenon where, after a seismic reflected wave passes through a high-velocity layer, its propagation speed increases, its travel time becomes relatively shorter, and an "upward protrusion" occurs beneath the high-velocity geological body. Specifically, for example... Figures 4A-4B As shown, Figure 4A This is a schematic diagram of a geological model of the upward protrusion state provided in an embodiment of this application. Figure 4B The technical principle diagram for the eyeball effect at the bottom boundary of the high-speed geological body provided in this application embodiment should be noted as follows: Figure 4B for Figure 4A The diagram shows the technical principle behind the eyeball effect corresponding to the geological model shown.

[0057] For example, Figure 4A The horizontal axis, vertical axis, numbers 1-5, and horizontal lines in the diagram represent the following meanings: Figure 3ASimilarly, without going into detail here, geological layers 1-5 correspond to the propagation speeds of V1'-V5' respectively. The propagation speeds of V2', V3', V4', and V5' are similar, while the propagation speed of V1' is less than that of V2'.

[0058] Figure 4B The horizontal axis, vertical axis, and numbers 1-5 in the text represent the meaning of... Figure 3B The same applies here, so I won't repeat it again. The horizontal line is the boundary between geological layer 1 and geological layer 2, and the curve is the boundary between geological layer 2, geological layer 3, geological layer 4 and geological layer 5. The above boundary lines can represent the bottom boundary of the geological body of geological layers 1-4. Because the propagation speed of seismic reflected waves increases after passing through geological layers 2, 3 and 4, and the travel time becomes relatively shorter, the boundary between geological layer 2 and geological layer 3 shows an upward phenomenon, the boundary between geological layer 3 and geological layer 4 shows an upward phenomenon, and the boundary between geological layer 4 and geological layer 5 shows an upward phenomenon. Therefore, this upward phenomenon is the eyeball effect of the upward protrusion state (i.e., false anticline).

[0059] An indistinct state can refer to a situation where the propagation speed of seismic reflected waves does not change significantly when they pass through geological layers, the travel time does not change significantly, and there are no obvious phenomena at the bottom boundary of the geological body.

[0060] The low-velocity layer can refer to the geological layer through which the fluid passes, where the propagation speed of seismic reflected waves is low, approximately 600-800 m / s; the high-velocity layer can refer to the geological layer through which the surrounding rock passes, where the propagation speed of seismic reflected waves is high, approximately 4000-5000 m / s.

[0061] Understandably, the propagation speeds differ between low-speed and high-speed layers due to the different media present. These different media affect the reservoir's productivity. For example, a reservoir with a high concentration of oil will have a slower propagation speed; if it contains water, the propagation speed will be faster. Therefore, a reservoir in a downward-sloping state will have a higher productivity; a reservoir in an upward-sloping state will have a moderate productivity; and a reservoir in an indistinct state will have a lower productivity.

[0062] In this embodiment of the application, the protruding direction can refer to the concave and convex direction of the outline of the beads with the ground surface as a reference frame. The ground surface is horizontal. Compared with the ground surface, the protruding direction is upward convex (upward protrusion) and downward concave (downward drift).

[0063] For example, the bead pattern of a reservoir to be tested can be obtained based on well logging data and seismic data of a certain reservoir. For instance, the bead pattern of the reservoir to be tested can be a downward drifting state.

[0064] S203. Based on the pre-obtained correspondence between the reservoir capacity and the bead pattern, predict the capacity of the reservoir to be tested.

[0065] In this embodiment of the application, the correspondence can refer to the relationship between the storage capacity of a reservoir and the bead pattern obtained through numerous experiments, wherein each bead pattern corresponds to the storage capacity of a reservoir. For example, if the bead pattern of a certain storage reservoir is a downward floating state, then the storage capacity of that reservoir can be determined to be 20,000 tons.

[0066] For example, the capacity of the storage tank to be tested can be predicted based on the pre-obtained correspondence between the storage tank capacity and the bead pattern. For instance, if the bead pattern of the storage tank to be tested is in a downward floating state, according to the pre-obtained correspondence, if the storage tank is in a downward floating state, then the capacity of the storage tank is 20,000 tons. Therefore, the capacity of the storage tank to be tested is predicted to be 20,000 tons.

[0067] Therefore, based on the well logging and seismic data of the reservoir to be tested, the beaded pattern of the reservoir can be obtained. Furthermore, based on the pre-obtained correspondence between the reservoir's production capacity and the beaded pattern, the production capacity of the reservoir to be tested can be predicted. Thus, this method can predict the production capacity of the reservoir to be tested in advance, thereby improving the efficiency of drilling out oil and gas.

[0068] In one possible implementation, the beaded morphology of the reservoir to be measured is obtained based on well logging data and seismic data. Figure 5 This is a schematic diagram of the process for obtaining the beaded shape of the reservoir to be tested, provided in an embodiment of this application. Figure 5 As shown, the process may include the following:

[0069] S501. Based on well logging data and seismic data, determine the outline of the beads in the reservoir to be measured.

[0070] In this embodiment of the application, the outline of the beads can refer to the outer edge lines that constitute the reservoir. With the horizontal plane of the ground as a reference, the beads can be divided according to the concave and convex lines into the outlines of convex curves, concave curves and indistinct curves.

[0071] For example, the outline of the beads of the reservoir to be measured can be determined manually based on well logging data and seismic data. For instance, the determined outline of the beads of the reservoir to be measured can be a concave curve.

[0072] S502. Based on the curvature corresponding to the contour, the beaded shape of the storage group to be tested is obtained.

[0073] In this embodiment of the application, curvature can refer to the rate of rotation of the tangent direction angle with respect to the arc length at a certain point on the curve, and is used to measure the degree of unevenness of the beads.

[0074] For example, the bead shape of the reservoir to be tested can be obtained based on the curvature corresponding to the outline of the beads. For instance, the curvature of the convex curve indicates that the bead shape of the reservoir to be tested is in an upward convex state, the curvature of the concave curve indicates that the bead shape of the reservoir to be tested is in a downward floating state, and the curvature of the indistinct curve indicates that the bead shape of the reservoir to be tested is indistinct.

[0075] Optionally, a section of curve located in the middle of the horizontal direction in the outline of the beaded string can be extracted. If the curvature of the curve is within the first interval, it can be considered to be in a downward drift state. If the curvature of the curve is within the second interval, it can be considered to be in an upward bulge state. If the curvature of the curve is within the third interval, it can be considered to be in an inconspicuous state.

[0076] It is understandable that when the protrusion of the bead outline changes, the corresponding curvature changes accordingly. Therefore, the concavity and convexity of the bead outline can be determined based on the curvature, and the shape of the bead can be further determined.

[0077] It should be noted that the first interval, the second interval, and the third interval can be determined according to actual needs, and the specific values ​​of the first interval, the second interval, and the third interval are not specifically limited in this application embodiment.

[0078] Optionally, the obtained outline can be displayed to the user. After seeing the display status of the outline, the user can input the corresponding status information of the outline. The status information can be a downward floating state, an upward protruding state, or an inconspicuous state. Furthermore, the bead pattern of the storage group can be determined by obtaining the status information input by the user.

[0079] Therefore, the outline of the beaded structure of the reservoir to be measured can be obtained through well logging data and seismic data. Furthermore, the morphology of the reservoir to be measured can be determined based on the curvature of the outline, which can accurately classify the beaded structure and improve the identification rate of the reservoir.

[0080] In one possible implementation, the bead pattern includes at least one of the following: a downward drifting state, an upward protrusion state, or an indistinct state. Based on the pre-obtained correspondence between the reservoir's production capacity and the bead pattern, the production capacity of the reservoir to be tested is predicted, including at least one of the following: if the bead pattern corresponding to the reservoir is a downward drifting state, then the reservoir is predicted to be a high-efficiency well, and the production capacity of the high-efficiency well is greater than a first threshold; if the bead pattern corresponding to the reservoir is an upward protrusion state, then the reservoir's production capacity is a medium-efficiency well, and the production capacity of the medium-efficiency well is greater than a second threshold, wherein the first threshold is greater than the second threshold; if the bead pattern corresponding to the reservoir is an indistinct state, then the reservoir's production capacity is a low-efficiency well, and the production capacity of the low-efficiency well is less than the second threshold.

[0081] In this embodiment of the application, a high-efficiency well can refer to the single-well productivity corresponding to a reservoir in a downdraft state. This high-efficiency well has a large oil and gas production capacity. Specifically, Figure 6 A cross-sectional schematic diagram of an efficient well provided in this application embodiment, as shown below. Figure 6 As shown, the reservoir in region 601 is a high-efficiency well. Furthermore, it can be seen that the beaded patterns corresponding to high-efficiency wells 602 and 603 are both in a downward drifting state.

[0082] Medium-efficiency wells can refer to single-well production capacity corresponding to a reservoir in a surging state. The oil and gas production capacity of such medium-efficiency wells is generally... Figure 7 A cross-sectional schematic diagram of a medium-efficiency well provided in an embodiment of this application, as shown below. Figure 7 As shown, the reservoir in area 701 is a medium-efficiency well. Furthermore, it can be seen that the beaded morphology corresponding to medium-efficiency well 702 is all in an upward protrusion state.

[0083] An inefficient well can refer to a single well with low production capacity when the reservoir is not clearly defined. Such an efficient well has a relatively small oil and gas production capacity. Figure 8 A cross-sectional schematic diagram of an inefficient well provided in this application embodiment, as shown below. Figure 8 As shown, the reservoirs in region 801 are inefficient wells. Furthermore, it can be seen that the beaded patterns corresponding to inefficient well 802 are all indistinct.

[0084] In this embodiment of the application, the first threshold may refer to a theoretical production value that can be used to evaluate a highly efficient well, obtained through multiple experiments. For example, the first threshold may be 20,000 tons. The second threshold may refer to a theoretical production value that can be used to evaluate medium-efficiency and low-efficiency wells, obtained through multiple experiments. For example, the second threshold may be 2,000 tons.

[0085] For example, a correlation can be established between the bead pattern of a reservoir and its production capacity. Furthermore, if the bead pattern of a reservoir is in a downward floating state, it can be predicted that the reservoir's production capacity is a high-efficiency well, and the production capacity of a high-efficiency well is greater than a first threshold, for example, the production capacity of a high-efficiency well is greater than 20,000 tons.

[0086] Optionally, if the beaded shape corresponding to the reservoir is in an upward protrusion state, then the reservoir capacity corresponding to the reservoir can be predicted to be a medium-efficiency well. The capacity of a medium-efficiency well is greater than the second threshold and less than the first threshold. For example, the first threshold can be 20,000 tons and the second threshold can be 2,000 tons.

[0087] Optionally, if the bead pattern corresponding to the reservoir is not obvious, it can be predicted that the reservoir capacity corresponding to the reservoir is an inefficient well. The capacity of an inefficient well is less than a second threshold, for example, the second threshold can be 0.2 million tons.

[0088] Therefore, based on the pre-obtained correspondence between reservoir capacity and bead pattern, the capacity of the reservoir to be tested can be predicted by the bead pattern of the reservoir to be tested. This can accurately predict the capacity provided by new drilling and improve drilling efficiency.

[0089] In this embodiment of the application, setting the first threshold to 20,000 tons and the second threshold to 2,000 tons is a reasonable result obtained through a large number of experiments.

[0090] For example, among the 85 wells surveyed, 25 were predicted to be high-efficiency wells (i.e., wells with a production capacity greater than 20,000 tons), and the final exploration results showed that 22 of them were successful, with an efficiency rate of 88%; 26 were predicted to be medium-efficiency wells (i.e., wells with a production capacity of 2,000 to 20,000 tons), and the final exploration results showed that 15 of them were successful, with an efficiency rate of 58%; and 34 were predicted to be low-efficiency wells (i.e., wells with a production capacity of less than 2,000 tons), and the final exploration results showed that 24 of them were successful, with an efficiency rate of 70%.

[0091] Therefore, setting the first threshold to 20,000 tons and the second threshold to 2,000 tons allows for a reasonable matching of high-efficiency, medium-efficiency, and low-efficiency wells with production capacity.

[0092] In one possible implementation, Figure 9 This application provides a schematic flowchart illustrating the correspondence between the production capacity of multiple storage tanks and their bead-like configurations. Figure 9 As shown, it may also include the following steps:

[0093] S901: Obtain well logging data and seismic data from multiple reservoirs within the block.

[0094] For example, if there are multiple reservoirs in a block, well logging data and seismic data of multiple reservoirs in the block can be obtained. This step is similar to S201, except that well logging data and seismic data of multiple reservoirs in a block are obtained, which will not be described in detail here.

[0095] S902. Based on well logging and seismic data from multiple reservoirs, the beaded morphology of multiple reservoirs is obtained.

[0096] For example, the beaded morphology of multiple reservoirs can be obtained based on well logging and seismic data. For instance, the beaded morphology of multiple reservoirs to be tested can all be in a downward drifting state, all be in an upward protruding state, or a mixture of upward protruding, downward drifting, and indistinct states.

[0097] S903. Based on the beaded pattern of multiple reservoirs and the cumulative production information corresponding to multiple reservoirs, establish a correspondence between the production capacity of a reservoir and the beaded pattern; wherein, this correspondence is used to predict the production capacity of the reservoir to be tested within the block.

[0098] In this embodiment of the application, the cumulative production information can refer to the cumulative production information of multiple storage collectives. For example, if there are 10 storage collectives in a certain block, and the corresponding production of these 10 storage collectives is 10,000 tons, 1,000 tons, 3,000 tons, 20,000 tons, 11,000 tons, 8,000 tons, 6,000 tons, 23,000 tons, 14,000 tons, and 18,000 tons respectively, then the cumulative production information of these 10 storage collectives is 114,000 tons.

[0099] For example, a correspondence between the capacity of a storage group and the bead pattern can be established based on the bead pattern of multiple storage groups and the cumulative production information of the corresponding storage groups. For instance, if multiple storage groups in a certain block have one downward drift state and two indistinct states, then the correspondence between the capacity of the storage group and the bead pattern can be established based on the bead pattern of the multiple storage groups and the cumulative production information of the corresponding storage groups.

[0100] Optionally, the beading patterns of multiple reservoirs can be obtained. These beading patterns can be in a downward floating state, an upward bulging state, or an indistinct state. Further, the production capacity corresponding to the beading patterns of these multiple reservoirs is listed separately, and the production capacity corresponding to the same pattern is weighted and calculated to obtain the cumulative production information of multiple reservoirs under the same state, thus establishing the correspondence between the production capacity of these multiple reservoirs and the beading patterns.

[0101] It should be noted that other methods for calculating the corresponding production capacity under the same condition can include averaging, taking the maximum value, etc., and the embodiments of this application do not specifically limit them.

[0102] For example, three storage groups in a downward drift state are obtained, with corresponding capacities of 20,000 tons, 24,000 tons, and 40,000 tons, respectively. The capacities corresponding to these downward drift states are weighted and calculated to obtain the cumulative production information of the three storage groups as 31,000 tons. Furthermore, a correspondence between the capacity of the three storage groups and the downward drift state can be established. If the capacity of multiple storage groups is greater than 30,000 tons, then the state corresponding to these multiple storage groups is the downward drift state.

[0103] Therefore, the embodiments of this application can also predict the production capacity of multiple reservoirs, effectively evaluate the production capacity of new wells, and have a wide range of applications.

[0104] In one possible implementation, the logging data includes at least one of the following: single well coordinates, wellbore depth, well inclination angle, logging information, lithological composition, and stratification status; based on the logging data and seismic data, the outline of the beaded structure of the reservoir to be measured is determined, including: acquiring the logging data and seismic data, and analyzing the outline of the beaded structure of the reservoir based on landmark software.

[0105] In this embodiment, the landmark software mainly consists of two parts: the OpenWorks software platform and various applications. Each application is a plugin for OpenWorks, runs within the OpenWorks environment, is managed by the OpenWorks software platform, and follows the rules and standards set by the OpenWorks software platform.

[0106] For example, an application can store various types of data from a reservoir, including well logging data and seismic data, in an OpenWorks database, forming a unified data volume. Further analysis can then reveal the outline of the reservoir's network of data.

[0107] Therefore, the embodiments of this application can obtain the outline of the beads in the storage group based on landmark software analysis, thereby improving the calculation accuracy and saving labor costs.

[0108] In the foregoing embodiments, the method for predicting the production capacity of carbonate fracture-vuggy reservoirs provided in this application has been introduced. To achieve the functions of the methods provided in the embodiments of this application, the electronic device serving as the execution entity may include hardware structures and / or software modules, implementing the aforementioned functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0109] For example, Figure 10 This is a schematic diagram of the structure of the carbonate rock fracture-vuggy reservoir capacity prediction device provided in the embodiments of this application, as shown below. Figure 10 As shown, the device 1000 includes: an acquisition module 1001, a processing module 1002, and a prediction module 1003; wherein, the acquisition module 1001 is used to acquire well logging data and seismic data of the reservoir to be tested; the processing module 1002 is used to obtain the bead pattern of the reservoir to be tested based on the well logging data and seismic data, the bead pattern being used to indicate the protruding direction of the bead outline; the prediction module 1003 is used to predict the production capacity of the reservoir to be tested based on the pre-obtained correspondence between the reservoir production capacity and the bead pattern.

[0110] In one possible implementation, the processing module 1002 is specifically used to determine the outline of the beads of the reservoir to be tested based on well logging data and seismic data; and to obtain the bead shape of the reservoir to be tested based on the curvature corresponding to the outline.

[0111] In one possible implementation, the bead pattern includes at least one of the following: a downward drifting state, an upward protrusion state, or an indistinct state; the prediction module 1003 is specifically used to predict the production capacity of the reservoir to be tested based on the pre-obtained correspondence between the reservoir's production capacity and the bead pattern, including at least one of the following: if the bead pattern corresponding to the reservoir is a downward drifting state, then the predicted production capacity of the reservoir corresponding to the reservoir is a high-efficiency well, and the production capacity of the high-efficiency well is greater than a first threshold; if the bead pattern corresponding to the reservoir is an upward protrusion state, then the predicted production capacity of the reservoir corresponding to the reservoir is a medium-efficiency well, and the production capacity of the medium-efficiency well is greater than a second threshold, wherein the first threshold is greater than the second threshold; if the bead pattern corresponding to the reservoir is an indistinct state, then the predicted production capacity of the reservoir corresponding to the reservoir is an inefficient well, and the production capacity of the inefficient well is less than the second threshold.

[0112] In one possible implementation, the first threshold is 20,000 tons and the second threshold is 2,000 tons.

[0113] In one possible implementation, the acquisition module 1001 is further configured to acquire well logging data and seismic data of multiple reservoirs within the block; the processing module 1002 is further configured to obtain the beaded pattern of multiple reservoirs based on the well logging data and seismic data of multiple reservoirs; and establish a correspondence between the reservoir production capacity and the beaded pattern based on the beaded pattern of multiple reservoirs and the cumulative production information corresponding to multiple reservoirs; wherein the correspondence is used to predict the production capacity of the reservoir to be measured within the block.

[0114] In one possible implementation, the logging data includes at least one of the following: single well coordinates, wellbore depth, well inclination angle, logging information, lithological composition, and stratification status; the acquisition module 1001 is further used to determine the outline of the beaded structure of the reservoir to be measured based on the logging data and seismic data, including: acquiring the logging data and seismic data, and analyzing the outline of the beaded structure of the reservoir based on landmark software.

[0115] This application also provides a schematic diagram of the structure of an electronic device. Figure 11 This application provides a schematic diagram of the structure of an electronic device, such as... Figure 11 As shown, the electronic device may include: a processor 1101 and a memory 1102; the memory 1102 stores a computer program; the processor 1101 executes the computer program stored in the memory 1102, causing the processor 1101 to perform the method described in any of the above embodiments.

[0116] The memory 1102 and the processor 1101 can be connected via bus 1103.

[0117] The specific implementation principle and effects of the carbonate rock fissure cavern type reservoir production capacity prediction device provided in this application embodiment can be found in the relevant descriptions and effects of the above embodiments, and will not be elaborated further here.

[0118] This application also provides a computer-readable storage medium storing computer program execution instructions. When executed by a processor, the computer program is used to enable a server to perform a carbonate rock fracture-vuggy reservoir production prediction method as described in any of the foregoing embodiments of this application.

[0119] This application also provides a chip for executing instructions, which is used to perform the carbonate rock fracture-vuggy reservoir production prediction method executed by electronic devices as in any of the foregoing embodiments of this application.

[0120] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements a method for predicting the production capacity of carbonate fracture-vuggy reservoirs as described in any of the foregoing embodiments of this application.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0122] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0123] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0124] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention.

[0125] It should be understood that the aforementioned processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0126] The memory may include high-speed random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0127] The bus can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0128] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0129] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and storage medium can exist as discrete components in an electronic device or host device.

[0130] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the claims.

Claims

1. A method for predicting the productivity of carbonate fracture-vuggy reservoirs, characterized in that, include: Acquire well logging and seismic data of the reservoir to be tested; Based on the well logging data and the seismic data, the beaded pattern of the reservoir to be measured is obtained, and the beaded pattern is used to indicate the protruding direction of the outline of the beads; Based on the pre-obtained correspondence between the storage capacity of the reservoir and the bead pattern, the capacity of the reservoir to be tested is predicted. Based on the well logging data and the seismic data, the beaded morphology of the reservoir to be measured is obtained, including: Based on the well logging data and the seismic data, the outline of the beads in the reservoir to be measured is determined; Based on the curvature corresponding to the contour, the beaded shape of the reservoir to be tested is obtained.

2. The method according to claim 1, characterized in that, The beaded morphology includes at least one of the following: downward floating state, upward protruding state, and indistinct state; based on the pre-obtained correspondence between the reservoir's capacity and the beaded morphology, the capacity of the reservoir to be tested is predicted, including at least one of the following: If the bead pattern corresponding to the reservoir is in a downward floating state, then the reservoir production capacity corresponding to the reservoir is predicted to be a high-efficiency well, and the production capacity of the high-efficiency well is greater than the first threshold. If the beaded shape corresponding to the reservoir is in an upward protrusion state, then the reservoir production capacity corresponding to the reservoir is predicted to be a medium-efficiency well, and the production capacity of the medium-efficiency well is greater than a second threshold, wherein the first threshold is greater than the second threshold; If the beaded pattern corresponding to the reservoir is not obvious, then the reservoir production capacity corresponding to the reservoir is predicted to be an inefficient well, and the production capacity of the inefficient well is less than the second threshold.

3. The method according to claim 2, characterized in that, The first threshold is 20,000 tons, and the second threshold is 2,000 tons.

4. The method according to any one of claims 1-3, characterized in that, Also includes: Acquire well logging and seismic data from multiple reservoirs within the block; Based on the well logging data and seismic data of the multiple reservoirs, the beaded pattern of the multiple reservoirs is obtained; Based on the beaded pattern of the multiple reservoirs and the cumulative production information corresponding to the multiple reservoirs, a correspondence between the reservoir capacity and the beaded pattern is established. The correspondence is used to predict the production capacity of the storage group to be tested within the block.

5. The method according to claim 1, characterized in that, The logging data includes at least one of the following: single well coordinates, wellbore depth, well inclination angle, logging information, lithological composition, and stratification status; Based on the well logging data and the seismic data, the outline of the beaded structure of the reservoir to be measured is determined, including: The well logging data and the seismic data are acquired, and the outline of the beaded structure of the reservoir is obtained based on the landmark software analysis.

6. A device for evaluating the productivity of carbonate rock fissure-vuggy reservoirs, characterized in that, include: The acquisition module is used to acquire well logging data and seismic data of the reservoir to be tested; The processing module is used to obtain the beaded shape of the reservoir to be measured based on the well logging data and the seismic data, wherein the beaded shape is used to indicate the protruding direction of the outline of the beads; The prediction module is used to predict the capacity of the storage tank to be tested based on the pre-obtained correspondence between the capacity of the storage tank and the bead pattern. The processing module is specifically used to determine the outline of the beaded structure of the reservoir to be tested based on the well logging data and the seismic data; and to obtain the beaded shape of the reservoir to be tested based on the curvature corresponding to the outline.

7. An electronic device, characterized in that, include: A processor, a memory, and a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor, the computer program including instructions for performing the carbonate fracture-vuggy reservoir productivity prediction method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the carbonate rock fracture-vuggy reservoir production prediction method as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for predicting the production capacity of carbonate fractured-vuggy reservoirs as described in any one of claims 1-5.

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