Lithofacies prediction method and device based on indication curve

Abstract

The invention provides a lithofacies prediction method and device based on an indication curve. According to the method, the effective combination of the seismic data information and the logging data information is realized by utilizing the indication curve, the accuracy and meticulous property of lithofacies prediction are obviously improved, and the prediction result has clear geological significance and can reflect the actual lithofacies distribution of volcanic rocks; the prediction of the three-dimensional space distribution rule of the lithofacies, especially the volcanic rock lithofacies, is realized, and the method has important value for volcanic rock exploration.

Description

Technical Field

[0001] The present invention relates to the field of geophysical prospecting technology, and more specifically, to a lithofacies prediction method and device based on an indicator curve. Background Art

[0002] According to the statistical analysis of a large number of researchers, volcanic reservoirs are significantly controlled by lithology, so the prediction of volcanic lithofacies is very important. Volcanic rocks are highly heterogeneous, especially the volcanic lithofacies belt changes very quickly. This poses a great challenge to accurately predict the spatial distribution of volcanic lithofacies. At present, there are two main approaches to lithofacies prediction, namely, based on post-stack seismic attributes and logging data interpretation, but both methods have certain defects and shortcomings.

[0003] Lithofacies prediction based on post-stack seismic attributes mainly relies on extracting multiple post-stack seismic attributes reflecting different lithofacies and fusing the attributes to identify lithofacies. Moreover, what is formed by seismic attributes is seismic facies, not lithofacies in the true sense. However, the differences in seismic response characteristics of different lithofacies are usually not very large, and it is difficult to effectively distinguish them only from seismic attributes. In addition, the resolution limitation of seismic methods cannot reflect the rapid change characteristics of lithofacies in detail. These factors make it difficult to clearly and accurately identify and describe the changes in volcanic lithofacies belts based solely on seismic data.

[0004] The method of lithofacies interpretation based on logging data is mainly to complete lithofacies division within the well section by identifying various logging curves that can reflect the characteristics of different lithofacies, such as acoustic, density, electrical and other curves. However, this method is limited to the well section and it is difficult to expand horizontally to achieve regional prediction. In addition, in some cases, the role of logging curve characteristics in indicating lithofacies also has certain limitations.

[0005] In general, existing lithofacies prediction methods rely on either seismic data or logging data, but they all have their own limitations and it is difficult to achieve accurate and reliable high-resolution prediction of the complex three-dimensional spatial distribution of volcanic lithofacies. Therefore, a technology that can more accurately predict lithofacies is needed to better guide the effective development of volcanic oil and gas reservoirs. Summary of the invention

[0006] In view of this, the present invention aims to propose a technical solution for integrating multi-source data to predict the three-dimensional distribution of lithofacies, so as to improve the accuracy of lithofacies interpretation.

[0007] According to one aspect of the present invention, a lithofacies prediction method based on an indicator curve is proposed, the method comprising:

[0008] Collect logging data from multiple wells in the target block and select electrical parameters D that indicate different lithofacies;

[0009] Collect 3D seismic data from multiple wells in the target block and select elastic parameters T to indicate different lithofacies;

[0010] According to the selected electrical parameter D and elastic parameter T, a lithofacies indicator curve L = D / T is constructed;

[0011] The constructed lithofacies indication curve L is constrained and based on waveform indication simulation, the three-dimensional distribution of lithofacies in the target block is predicted.

[0012] In some embodiments, the method further comprises:

[0013] If the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter D2 is selected to construct a modified indicator curve L2=D*D2 / T. The modified indicator curve L2 is constrained and the three-dimensional distribution of lithofacies in the target block is predicted based on waveform indication simulation.

[0014] In some embodiments, the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter, resistivity, natural potential, electromagnetic wave absorptivity or phase.

[0015] In some embodiments, the target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

[0016] In some embodiments, the elastic parameters selected to indicate different lithological phases are acoustic wave time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

[0017] In some embodiments, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic time difference.

[0018] In some embodiments, the predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0019] According to another aspect of the present invention, a lithology prediction device based on an indicator curve is provided, the device comprising:

[0020] An electrical parameter selection unit is used to collect logging data of multiple wells in the target block and select electrical parameters D for indicating different lithofacies;

[0021] An elastic parameter selection unit is used to collect three-dimensional seismic data from multiple wells in the target block and select elastic parameters T for indicating different lithofacies;

[0022] A lithofacies indication curve construction unit is used to construct a lithofacies indication curve L=D / T according to the selected electrical parameter D and elastic parameter T;

[0023] The lithofacies distribution prediction unit is used to predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation by constraining the constructed lithofacies indication curve L.

[0024] In some embodiments, the device also includes a second electrical parameter selection unit and a corrected indicator curve construction unit. Specifically, if the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter selection unit is used to select a second electrical parameter D2, and the corrected indicator curve construction unit is used to construct a corrected indicator curve L2=D*D2 / T. The lithofacies distribution prediction unit is also used to use the corrected indicator curve L2 for constraints and predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation.

[0025] In some embodiments, the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter, resistivity, natural potential, electromagnetic wave absorptivity or phase.

[0026] In some embodiments, the target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

[0027] In some embodiments, the elastic parameters selected to indicate different lithological phases are acoustic wave time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

[0028] In some embodiments, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic time difference.

[0029] In some embodiments, the predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0030] According to another aspect of the present invention, an electronic device is also provided, the electronic device comprising:

[0031] A memory storing executable instructions;

[0032] A processor runs the executable instructions in the memory to implement the above-mentioned lithology prediction method based on indicator curves.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned lithofacies prediction method based on indicator curves is implemented.

[0034] The beneficial effects of the present invention include:

[0035] 1. The indicator curve is used to effectively combine seismic data and logging data, thus improving the accuracy of lithofacies prediction;

[0036] 2. The prediction results have clear geological significance and can reflect the actual lithofacies distribution of volcanic rocks;

[0037] 3. The prediction of the three-dimensional spatial distribution of lithofacies, especially volcanic lithofacies, has been realized, which is of great value to volcanic rock exploration.

[0038] The methods and apparatus of the present invention have other features and advantages that will be apparent from or will be described in detail in the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0040] Figure 1 A flow chart of a lithology prediction method based on an indicator curve according to an embodiment of the present invention is shown.

[0041] Figure 2 A histogram showing the relationship between multiple parameters and different lithologies according to an embodiment of the present invention is shown.

[0042] Figure 3 A histogram showing the relationship between a facies indication curve and different facies according to an embodiment of the present invention is shown.

[0043] Figure 4 A comparison diagram of the lithofacies prediction results and the lithofacies geological results according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0045] Example 1

[0046] Figure 1The flowchart of the method for facies prediction based on indicator curves according to an embodiment of the present invention is shown. As shown in the figure, the example includes steps 1 to 4.

[0047] Step 1: Collect logging data from multiple wells in the target block and select electrical parameters D that are used to indicate different lithofacies.

[0048] Logging data is an important data in the field of petroleum engineering, which is used to evaluate the properties and characteristics of underground oil and gas reservoirs. Logging is to obtain information related to underground reservoirs by using various logging tools to perform physical measurements and record data on the formations around the wellbore during the drilling process.

[0049] Well logging data provides information about important parameters such as formation composition, pore structure, porosity, permeability, fluid saturation, etc. These parameters are crucial for evaluating the potential of oil and gas reservoirs, determining oil production plans and predicting production. By analyzing well logging data, engineers can understand the nature of the reservoir, lithology, fluid type and fluid distribution in the reservoir.

[0050] Common logging tools include logging cables, logging heads, resistivity logging tools, natural gamma logging tools, acoustic logging tools, density logging tools, etc. These tools provide information on the different properties and characteristics of the formation by measuring physical parameters such as resistivity, natural gamma rays, acoustic wave propagation velocity, and density.

[0051] Well logging data is usually presented in the form of curves, where each curve represents a different measurement parameter. Engineers analyze these curves comprehensively, use geological models and mathematical methods, and interpret and explain them to obtain quantitative information about formation properties and reservoir characteristics.

[0052] In short, well logging data is the data obtained by using logging tools to perform physical measurements and data recording on the formation during the drilling process, which is used to evaluate the properties and characteristics of oil and gas reservoirs. It plays a vital role in oil and gas exploration and development, helping engineers make decisions and optimize oil and gas production.

[0053] Based on the logging data, multiple electrical parameters can be obtained, and then the relationship between different electrical parameter curves and lithofacies can be analyzed. For example, histograms of the relationship between different electrical parameter curves and lithofacies can be drawn respectively, and the electrical parameters that can effectively distinguish different lithofacies can be selected as the electrical parameters D used to construct the lithofacies indicator curve in the future.

[0054] The following is a brief description of several electrical parameters that can be obtained from logging data:

[0055] Gamma ray parameter (GR): indicates the natural radioactivity intensity of rock and reflects the amount of radiation contained in rock;

[0056] Resistivity (R): reflects the conductivity of rocks and is related to the porosity, water content and salinity of rocks;

[0057] Spontaneous potential (SP): Spontaneous potential uses the principle of natural batteries to measure the distribution of spontaneous potential in rocks. It reflects the corrosiveness, permeability and saturation characteristics of rocks.

[0058] Electromagnetic wave absorptivity (A): indicates the attenuation of electromagnetic waves when passing through rocks, which is related to the electrical conductivity and magnetic permeability of rocks;

[0059] Phase (P): It indicates the phase change of electromagnetic waves in rocks and reflects the conductivity distribution of rocks.

[0060] In addition, the electrical parameters that can be obtained based on logging data may also include rock density (DEN) and the like.

[0061] These electrical parameters play an important role in identifying lithology and determining strata, and are an important basis for lithofacies prediction. The inventor needs to conduct an in-depth analysis of the relationship between different electrical parameters and lithofacies in order to select electrical parameters that can effectively reflect lithofacies differences.

[0062] In some embodiments, the electrical parameters selected to indicate different lithofacies are gamma ray parameters, resistivity, natural potential, electromagnetic wave absorptivity or phase, etc. In particular, in some examples according to the present invention, the target block is volcanic rock, and the elastic parameters selected to indicate different lithofacies are acoustic wave time differences.

[0063] Step 2: Collect 3D seismic data from multiple wells in the target block and select elastic parameters T for indicating different lithofacies.

[0064] Seismic data is an important type of data obtained using seismic measurement technology in the field of seismic exploration. It is used to study underground structures, detect oil and gas resources, and assess earthquake risks.

[0065] Seismic exploration is carried out by placing seismic instruments on the surface or underwater, sending controlled seismic energy (such as blasting sources or seismic sources) underground, and recording the returned seismic wave signals. These seismic wave signals propagate at different speeds in the underground rocks and media, and are then received and recorded by the seismic instruments. By analyzing these recorded seismic wave signals, information such as the properties, structure, sequence and underground structure of the underground rocks can be inferred.

[0066] Seismic data is usually presented in the form of a seismic profile, where the horizontal axis represents distance or time and the vertical axis represents the amplitude or energy of the seismic wave signal. Seismic profiles can be two-dimensional (2D) or three-dimensional (3D), providing detailed information about underground structures.

[0067] Seismic data plays an important role in oil and gas exploration. By analyzing seismic data, seismologists and geologists can determine the location, morphology and properties of potential oil and gas reservoirs to help explorers choose appropriate drilling locations. In addition, seismic data can also be used to assess earthquake risks, predict earthquake activities, and provide data support for geological disaster research.

[0068] In short, seismic data is a record of seismic wave signals obtained through seismic exploration technology, which is used to study underground structures, detect oil and gas resources, and assess earthquake risks. It plays an important role in oil and gas exploration, geological research, and geological disaster prediction.

[0069] Based on the seismic data, multiple elastic parameters can be obtained, and then the relationship between different elastic parameter curves and lithofacies can be analyzed. For example, histograms of the relationship between different elastic parameter curves and lithofacies can be drawn respectively, and the elastic parameters that can effectively distinguish different lithofacies can be selected as the elastic parameters T used to construct the lithofacies indicator curve in the future.

[0070] The following is a brief description of several elastic parameters that can be obtained from logging data:

[0071] Acoustic time difference (DT): reflects the propagation time difference characteristics of sound waves, which is closely related to the longitudinal wave velocity Vp;

[0072] Shear wave velocity (Vs): Shear waves refer to the wave form of particle vibration perpendicular to wave propagation. Shear wave velocity is used to describe the speed at which sound waves propagate in rocks as shear waves.

[0073] P-wave velocity (Vp): P-wave refers to the wave form in which the particle vibration direction of the sound wave is consistent with the wave propagation direction. P-wave velocity is used to describe the speed at which the sound wave propagates in the rock as a longitudinal wave;

[0074] Density (DEN): Indicates the mass density of rock, which is related to the mineral composition and porosity of the rock;

[0075] Poisson's Ratio: It indicates the relationship between lateral strain and longitudinal strain and reflects the pore characteristics of rocks.

[0076] Rigidity: reflects the ability of rock to resist deformation and is related to the hardness of rock;

[0077] Stress parameter: The stress state in the rock, reflecting the fracture and aggregation state of the stratum;

[0078] Dispersion: The difference in the speed of sound waves of different frequencies reflects the absorption and scattering characteristics of rocks;

[0079] Acoustic wave damping (Attenuation): reflects the degree of attenuation of sound waves in rocks and is related to the porosity, water content, mineral composition, etc. of the rocks.

[0080] These elastic parameters can be extracted through the analysis of seismic records, which are important reflections of rock physical characteristics and can provide effective references for lithofacies prediction. The inventors need to conduct in-depth analysis of the relationship between different elastic parameters and lithofacies in order to select elastic parameters that can effectively reflect lithofacies differences.

[0081] In some embodiments, the elastic parameter selected to indicate different lithofacies is acoustic transit time, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter, etc. In particular, in some examples according to the present invention, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic transit time.

[0082] Step 3: construct a lithofacies indicator curve L=D / T according to the selected electrical parameter D and elastic parameter T.

[0083] After in-depth research, the inventor believes that according to the present invention, elastic parameters can serve as low-frequency background in lithofacies prediction, and electrical parameters D can well reflect lithofacies characteristics, so the obtained lithofacies indicator curve L can well distinguish lithofacies. In application, the constructed lithofacies indicator curve can be subjected to intersection analysis and histogram analysis to ensure the discrimination of the constructed indicator curve, that is, to accurately predict the three-dimensional distribution of lithofacies.

[0084] In some embodiments, the predicted three-dimensional distribution of lithofacies may be compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0085] In some embodiments, if the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter D2 is selected to construct a modified indicator curve L2=D*D2 / T, and the modified indicator curve L2 is constrained to predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation.

[0086] According to this embodiment, when the constructed lithofacies indicator curve can effectively distinguish different lithofacies, the indicator curve adopts a single electrical parameter, that is, a single electrical parameter D is used as the numerator of the indicator curve; when the single electrical indicator curve cannot effectively distinguish different lithofacies, a second electrical parameter D2 is added to correct the indicator curve until the obtained corrected indicator curve can effectively distinguish different lithofacies, thereby further improving the accuracy and adaptability of the lithofacies prediction according to the present invention.

[0087] If the target block is volcanic rock, the identified lithofacies can usually include eruptive phase, sedimentary phase, sedimentary rock phase, effusive phase, etc. In some blocks, it may also include vein phase, pipe burst phase, pyroclastic phase, volcanic mudflow phase, etc. The following is a brief introduction to the lithofacies of volcanic rocks.

[0088] From the perspective of the genesis and formation process of volcanic rocks, the lithofacies of Jingshang volcanic rocks can be divided into:

[0089] Eruptive phase: refers to the magma phase ejected during a volcanic eruption. This part of the magma cools rapidly to form a glassy pyroclastic layer;

[0090] Sedimentary phase: refers to the sequence formed by the accumulation of volcanic debris under the action of gravity after the eruption, such as volcanic tuff, volcanic gravel, etc.

[0091] Sedimentary facies: refers to sedimentary volcanic rock layers formed by re-deposition and diagenesis by water flow, such as volcanic siltstone;

[0092] Effusive phase: refers to the rock body formed by the cooling of magma after it is discharged in a gentle flow, such as pyroxene and rhyolite;

[0093] Dike phase: refers to the dikes formed when magma invades other rocks through cracks, which often have a porous structure;

[0094] Explosive pipe phase: refers to the narrow rock bodies such as volcanic necks formed by the eruption of magma through channels;

[0095] Pyroclastic phase: contains various pyroclastics, volcanic bombs and other sediments;

[0096] Lahar facies: mudflow deposits formed by a mixture of volcanic debris and water.

[0097] The above classification emphasizes the causal process, which helps to analyze the history of volcanic eruptions and sedimentation, and has guiding significance for the study of the laws of volcanic rock accumulation.

[0098] According to the present invention, the lithofacies of volcanic rocks can be effectively predicted. Different lithofacies represent different causes and formation processes of volcanic rocks. Accurate identification of lithofacies is helpful to explain the history of volcanic eruptions and sedimentation. The identification results are of great significance to the reservoir-forming laws of volcanic rocks.

[0099] Step 4: Use the constructed lithofacies indication curve L to constrain the seismic data and predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation.

[0100] Waveform Modeling can be used to simulate the propagation process of seismic waves in underground media and the generated waveform response.

[0101] Waveform indication simulation is to calculate and predict the propagation path and waveform response of seismic waves underground based on known underground medium models and seismic instrument parameters through mathematical modeling and calculation methods. It can simulate the propagation speed, attenuation, reflection, refraction and other phenomena of seismic waves in different media, as well as their interaction with underground structures.

[0102] Through waveform indication simulation, geophysicists can predict the propagation path and waveform response of seismic waves under different underground conditions. This is of great significance for understanding the characteristics of underground media, predicting the distribution and interference of seismic waves underground, interpreting seismic data, and optimizing exploration and development strategies.

[0103] Waveform indication simulation is usually based on numerical methods, such as the finite difference method, the finite element method or the radiation modeling method. These methods use numerical algorithms to solve the seismic wave equation and calculate the propagation path and waveform response of the seismic wave in the underground.

[0104] In short, waveform indication simulation is a geophysical exploration technology that simulates the propagation path and waveform response of seismic waves in underground media through mathematical modeling and calculation methods. It plays an important role in seismic wave interpretation, underground structure research and exploration and development.

[0105] In the present invention, the inventors construct a lithofacies indicator curve L (in some examples, a modified indicator curve L2) based on waveform indication simulation, which can effectively predict the three-dimensional distribution of lithofacies in the target block.

[0106] In summary, according to the technical solution of this embodiment, the indicator curve is used to realize the effective combination of seismic data information and logging data information, which significantly improves the accuracy and meticulousness of lithofacies prediction. The prediction results have clear geological significance, can reflect the actual lithofacies distribution of volcanic rocks, and realize the prediction of lithofacies, especially the three-dimensional spatial distribution law of volcanic rock lithofacies, which is of great value to volcanic rock exploration.

[0107] Example 2

[0108] The present invention also proposes a lithofacies prediction device based on an indicator curve, the device comprising:

[0109] An electrical parameter selection unit is used to collect logging data of multiple wells in the target block and select electrical parameters D for indicating different lithofacies;

[0110] An elastic parameter selection unit is used to collect 3D seismic data from multiple wells in the target block and select elastic parameters T for indicating different lithofacies;

[0111] A lithofacies indication curve construction unit is used to construct a lithofacies indication curve L=D / T according to the selected electrical parameter D and elastic parameter T;

[0112] The lithofacies distribution prediction unit is used to predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation by constraining the constructed lithofacies indication curve L.

[0113] In some embodiments, the device also includes a second electrical parameter selection unit and a corrected indicator curve construction unit. Specifically, if the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter selection unit is used to select a second electrical parameter D2, and the corrected indicator curve construction unit is used to construct a corrected indicator curve L2 = D*D2 / T. The lithofacies distribution prediction unit is also used to use the corrected indicator curve L2 for constraints, and based on waveform indication simulation, predict the three-dimensional distribution of lithofacies in the target block.

[0114] In some embodiments, the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter, resistivity, natural potential, electromagnetic wave absorptivity or phase.

[0115] In some embodiments, the target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

[0116] In some embodiments, the elastic parameters selected to indicate different lithological phases are acoustic wave time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

[0117] In some embodiments, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic time difference.

[0118] In some embodiments, the predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0119] For other detailed descriptions and advantages of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0120] Example 3

[0121] According to another aspect of the present invention, an electronic device is provided. The electronic device comprises:

[0122] A memory storing executable instructions;

[0123] A processor runs the executable instructions in the memory to implement the indicator curve-based lithology prediction method according to the present invention.

[0124] The method comprises the following steps 1 to 4.

[0125] The method comprises:

[0126] Step 1, collecting logging data of multiple wells in the target block, and selecting electrical parameters D for indicating different lithofacies;

[0127] Step 2, collecting 3D seismic data from multiple wells in the target block and selecting elastic parameters T for indicating different lithofacies;

[0128] Step 3, constructing a lithofacies indicator curve L=D / T according to the selected electrical parameter D and elastic parameter T;

[0129] Step 4: Constrained by the constructed lithofacies indication curve L, based on waveform indication simulation, predict the three-dimensional distribution of lithofacies in the target block.

[0130] In some embodiments, the method further comprises:

[0131] If the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter D2 is selected to construct a modified indicator curve L2=D*D2 / T. The modified indicator curve L2 is constrained and the three-dimensional distribution of lithofacies in the target block is predicted based on waveform indication simulation.

[0132] In some embodiments, the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter, resistivity, natural potential, electromagnetic wave absorptivity or phase.

[0133] In some embodiments, the target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

[0134] In some embodiments, the elastic parameters selected to indicate different lithological phases are acoustic wave time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

[0135] In some embodiments, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic time difference.

[0136] In some embodiments, the predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0137] Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc.

[0138] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0139] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0140] Example 4

[0141] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the indicator curve-based lithology prediction method according to the present invention is implemented.

[0142] The method comprises the following steps 1 to 4.

[0143] The method comprises:

[0144] Collect logging data from multiple wells in the target block and select electrical parameters D that indicate different lithofacies;

[0145] Collect 3D seismic data from multiple wells in the target block and select elastic parameters T to indicate different lithofacies;

[0146] According to the selected electrical parameter D and elastic parameter T, a lithofacies indicator curve L = D / T is constructed;

[0147] The constructed lithofacies indication curve L is constrained and based on waveform indication simulation, the three-dimensional distribution of lithofacies in the target block is predicted.

[0148] In some embodiments, the method further comprises:

[0149] If the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter D2 is selected to construct a modified indicator curve L2=D*D2 / T. The modified indicator curve L2 is constrained and the three-dimensional distribution of lithofacies in the target block is predicted based on waveform indication simulation.

[0150] In some embodiments, the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter, resistivity, natural potential, electromagnetic wave absorptivity or phase.

[0151] In some embodiments, the target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

[0152] In some embodiments, the elastic parameters selected to indicate different lithological phases are acoustic wave time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

[0153] In some embodiments, the target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is acoustic time difference.

[0154] In some embodiments, the predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

[0155] The computer-readable storage medium according to the embodiment of the present invention stores non-transitory computer-readable instructions, and when the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of the embodiments of the present invention are executed.

[0156] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0157] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present invention.

[0158] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0159] Example 5

[0160] This example is illustrated by comparing the results of the lithofacies interpretation with the predicted lithofacies bodies of volcanic rocks based on indicator curves.

[0161] Figure 2The histogram of the relationship between the seismic response characteristics and electrical curve characteristics of different volcanic rock facies according to the present invention is shown. Among them, DT represents the acoustic time difference curve; CNL is a logging curve used to measure the hydrogen content in the formation. It estimates the hydrogen content by measuring the neutron scattering in the formation, thereby providing information about the porosity and fluid saturation of the formation; DEN represents the density curve; GR represents the gamma ray parameter curve; LLD is a logging curve that combines density logging and lithology logging. It uses two detectors with a long spacing to measure the density and natural gamma ray intensity of the formation respectively. By analyzing the LLD curve, the density and radioactive characteristics of the formation can be obtained, thereby inferring the rock type and composition.

[0162] In this example, the radioactive gamma parameter is selected as the electrical parameter D of the constructed curve, and the acoustic time difference is selected as the elastic parameter T of the constructed curve, both of which have significantly different characteristics in different lithofacies.

[0163] Then calculate the lithofacies indicator curves L = T / D of the three test wells in the target block, perform a histogram analysis on the indicator curves and volcanic rock facies, and make it clear that the indicator curves can distinguish different volcanic rock facies well, such as Figure 3 shown.

[0164] The spatial prediction of the entire lithofacies three-dimensional body is realized by constraining the lithofacies indication curves of multiple wells based on waveform indication simulation. The well volcanic rock lithofacies interpretation results obtained based on geological data are compared with the prediction results of the volcanic rock lithofacies body predicted based on the lithofacies indication curve L according to the present invention, as shown in FIG. Figure 4 As shown, it can be found that there is a good degree of consistency between the two, which fully demonstrates that according to the present invention, by constructing lithofacies indicator curves to predict volcanic rock facies, it is possible to predict volcanic rock facies phase bodies and make a good prediction of the spatial distribution of volcanic rock facies bodies. At the same time, the prediction results of the phase bodies have geological significance consistent with the actual situation.

[0165] For other detailed descriptions of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0166] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein are selected to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A lithofacies prediction method based on an indicator curve, characterized in that: The method comprises: Collect logging data from multiple wells in the target block and select electrical parameters D that indicate different lithofacies; Collect 3D seismic data from multiple wells in the target block and select elastic parameters T to indicate different lithofacies; According to the selected electrical parameter D and elastic parameter T, a lithofacies indicator curve L = D / T is constructed; The constructed lithofacies indication curve L is constrained and based on waveform indication simulation, the three-dimensional distribution of lithofacies in the target block is predicted.

2. The method according to claim 1, characterized in that: The method further comprises: If the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter D2 is selected to construct a modified indicator curve L2=D*D2 / T. The modified indicator curve L2 is constrained and the three-dimensional distribution of lithofacies in the target block is predicted based on waveform indication simulation.

3. The method according to claim 1, characterized in that The electrical parameters D selected to indicate different lithofacies are gamma ray parameters, resistivity, natural potential, electromagnetic wave absorptivity or phase.

4. The method according to claim 3, characterized in that: The target block is volcanic rock, and the electrical parameter D selected to indicate different lithofacies is a gamma ray parameter.

5. The method according to claim 1, characterized in that The elastic parameters selected to indicate different lithofacies are acoustic time difference, shear wave velocity, longitudinal wave velocity, density, Poisson's ratio, rigidity parameter or stress parameter.

6. The method according to claim 5, characterized in that The target block is volcanic rock, and the elastic parameter selected to indicate different lithofacies is the acoustic time difference.

7. The method according to claim 1, characterized in that The predicted three-dimensional distribution of lithofacies is compared with the lithofacies geological results in the target block to verify the predicted three-dimensional distribution of lithofacies.

8. A lithofacies prediction device based on an indicator curve, characterized in that: The device comprises: An electrical parameter selection unit is used to collect logging data of multiple wells in the target block and select electrical parameters D for indicating different lithofacies; An elastic parameter selection unit is used to collect 3D seismic data from multiple wells in the target block and select elastic parameters T for indicating different lithofacies; A lithofacies indication curve construction unit is used to construct a lithofacies indication curve L=D / T according to the selected electrical parameter D and elastic parameter T; The lithofacies distribution prediction unit is used to predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation by constraining the constructed lithofacies indication curve L.

9. The device according to claim 8, characterized in that The device also includes a second electrical parameter selection unit and a corrected indicator curve construction unit. Specifically, if the constructed lithofacies indicator curve L cannot distinguish different lithofacies, the second electrical parameter selection unit is used to select a second electrical parameter D2, and the corrected indicator curve construction unit is used to construct a corrected indicator curve L2=D*D2 / T. The lithofacies distribution prediction unit is also used to use the corrected indicator curve L2 for constraints and predict the three-dimensional distribution of lithofacies in the target block based on waveform indication simulation.

10. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the method according to any one of claims 1 to 7.

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