Small-scale igneous rock wall identification method based on seismic data and production data
By combining seismic data and production data, and utilizing seismic attribute data and well network characteristics, the distribution map of small-scale igneous dikes is dynamically corrected, solving the problem of difficulty in identifying small-scale igneous dikes in existing technologies, and improving oilfield development efficiency and the accuracy of reserve calculation.
Patent Information
- Application Number
- CN202511493831.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-20
- Publication Date
- 2026-01-16
AI Technical Summary
The lack of existing methods for identifying small-scale igneous dikes leads to low development efficiency in oilfields in igneous rock development areas, making it difficult to accurately characterize small-scale igneous bodies and affecting reserve calculations and development plan preparation.
By combining seismic data and production data, static identification and dynamic correction are performed using seismic attribute data to establish a distribution map of small-scale igneous dikes. This includes the identification of seismic profiles, variance volume attributes, and root mean square amplitude attributes. Furthermore, by fitting the well network characteristics and double logarithmic curves of pressure integral derivatives, igneous dikes can be dynamically identified.
It enables accurate identification of small-scale igneous dikes, improves the development efficiency of oilfields in igneous development zones, and provides reliable guidance for development plans.
Smart Images
Figure CN121348422A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of petroleum resource exploration and development technology, specifically relating to a method for identifying small-scale igneous dikes based on seismic data and production data. Background Technology
[0002] As exploration and development deepen, the exploration and development of oilfields in igneous rock development areas has gradually become an important direction for increasing reserves and production. Due to the influence of volcanic activity, the reservoir distribution and reservoir properties of these oilfields are significantly different from those of conventional oilfields. During volcanic activity, magma not only migrates and erupts through volcanic conduits to form large-scale igneous bodies, but also intrudes into the strata through faults and other fractures, forming numerous small-scale dikes. The development scale, distribution morphology, and impact on surrounding reservoirs of igneous rocks are closely related to the spatiotemporal relationship between faults, magma, and strata. These igneous dikes form seepage barriers, resulting in complex internal reservoir connectivity, difficulty in replenishing oilfield energy, and reduced development efficiency. Therefore, accurate characterization of igneous bodies at various scales is an important foundation for carrying out reserve calculations and developing development plans.
[0003] Current conventional methods for identifying igneous bodies rely on comparing igneous facies encountered in single wells to summarize igneous development patterns, which are then characterized using seismic profiles. However, this method is limited by the resolution of seismic data and can only identify larger-scale igneous bodies. For small-scale igneous dikes, identification remains difficult due to the limited number of oil and gas fields explored and developed in igneous development areas, insufficient research, and the lack of relevant identification methods. This hinders the efficient development of oil fields in igneous development areas.
[0004] Therefore, there is an urgent need to establish a method for identifying small-scale igneous dikes in igneous rock development areas. This method can easily, quickly, accurately, and reasonably identify small-scale igneous dikes, avoid their adverse effects, and guide the preparation and adjustment of oilfield development plans. Summary of the Invention
[0005] This invention addresses the lack of methods for identifying small-scale igneous dikes in igneous rock development zones and the low prediction accuracy in existing technologies. Its purpose is to provide a method for identifying small-scale igneous dikes based on seismic data and production data.
[0006] This invention is achieved through the following technical solution: A method for identifying small-scale igneous dikes based on seismic data and production data includes the following steps: S1. Based on the seismic data, geological data, and well logging data of the oilfield, clarify the spatiotemporal relationship of faults, magma, and sediments; Specifically, based on the geological background of the oilfield area, using the three-dimensional seismic and geological data of the oilfield, the periods of fault activity and igneous activity are divided. Based on the periods of fault activity and their extension scale, the periods and scale of igneous activity, as well as the time of stratigraphic deposition and oil and gas charging, the spatiotemporal relationship between faults, magma, and sediments is clarified. S2. Using different attribute data of seismic data, small-scale igneous dikes are identified statically from both planar and longitudinal perspectives. Specifically, the following steps are included: S21. On the seismic profile, small-scale igneous dikes are precisely identified, their locations are delineated, and the distribution of small-scale igneous dikes on the seismic profile is formed. S22. Establish the variance volume attribute of the seismic data volume, perform fine identification of small-scale igneous dikes on the variance attribute profile, delineate the location of small-scale igneous dikes, and form the distribution of small-scale igneous dikes on the variance profile. S23. Establish the root mean square amplitude attribute of the seismic data volume, and delineate the location of small-scale igneous dikes on the root mean square attribute plane to form a planar distribution of small-scale igneous dikes.
[0007] S3. Overlay the planar and longitudinal static identification results to classify the credibility of the small-scale igneous dikes identified by static identification. Specifically, the following steps are included: S31. Project the small-scale igneous dike distribution from the seismic profile and the small-scale igneous dike distribution from the variance profile onto the small-scale igneous dike distribution in the plane and overlay them. S32. Based on the degree of superposition of the rock walls delineated by different methods, the credibility is graded. Credibility is categorized into four levels: Level 1, Level 2, Level 3, and Level 4. Level 1: Small-scale igneous dikes identified by all three methods at the same location; Level 2 refers to small-scale igneous dikes identified by two methods at the same location: root mean square attribute and seismic profile or root mean square attribute and variance profile. Level 3 refers to small-scale igneous dikes identified by both seismic profiles and variance profiles at the same location. Level 4: Small-scale igneous dikes identified by only one method.
[0008] S4. Extract the characteristics of oilfield well network and establish a theoretical chart of double logarithmic curves of pressure integral derivative under different closed ranges; Specifically, based on the geological and reservoir characteristics of the target oilfield, geological and reservoir parameters are obtained, well spacing and injection-production parameter characteristics are extracted, different small-scale igneous dike distances are set, and double logarithmic curves of pressure integral derivatives under different closed ranges are established using the formulas for calculating dimensionless pressure integrals and their derivatives.
[0009] The formula for calculating the dimensionless pressure integral is as follows: In the formula: This is a dimensionless pressure integral; Dimensionless pressure; The time for dimensionless mass equilibrium; The formula for calculating the dimensionless pressure integral derivative is as follows: In the formula: The derivative of the dimensionless pressure integral, This is a dimensionless pressure integral; The time for dimensionless mass equilibrium; S5. Fit the actual production data with the theoretical chart to obtain the fitting parameters and dynamically identify small-scale igneous dikes. The theoretical chart is a double logarithmic curve chart of pressure integral derivative under different closed ranges established in step S4. Specifically, based on the historical pressure and production data of a single well, the dimensionless pressure integral and the dimensionless pressure integral derivative are calculated. The dimensionless pressure and the dimensionless pressure integral derivative curves of a single well are plotted on a double logarithmic plot and fitted with the double logarithmic curve of the pressure integral derivative obtained in step S4, so that each set of curves can obtain a good fit as much as possible. The fitting parameters are obtained to determine the igneous rock closure range and dynamically identify small-scale igneous rock dikes.
[0010] S6. Based on the dynamic identification results, correct the small-scale igneous dikes identified in the static identification. Specifically, based on the dynamic identification results of igneous dikes, the location, quantity, and length of the igneous dikes are corrected to determine the final small-scale distribution of igneous dikes; S7. Draw a small-scale distribution map of igneous dikes across the entire oilfield.
[0011] Specifically, based on the combined dynamic and static identification results (the final small-scale igneous dike distribution determined in step S6), a small-scale dike distribution map is drawn within the target oilfield area by layer.
[0012] The beneficial effects of this invention are: This invention provides a method for identifying small-scale igneous dikes based on seismic and production data. It clarifies the spatiotemporal relationships of faults, magma, and sedimentation based on oilfield seismic, geological, and well logging data. Utilizing different attribute data from seismic data, it statically identifies and classifies small-scale igneous dikes from both planar and vertical perspectives. It extracts oilfield well network characteristics and establishes theoretical charts of double logarithmic curves of pressure integral derivatives under different closed ranges. By fitting actual production data with the theoretical charts, it dynamically identifies small-scale igneous dikes and corrects the statically identified dikes, obtaining an accurate distribution of small-scale igneous dikes across the entire oilfield. This method combines dynamic and static approaches, resulting in high accuracy and a reasonable and reliable distribution of small-scale igneous dikes in igneous development zones. Attached Figure Description
[0013] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a small-scale igneous dike distribution map on the seismic profile in Embodiment 1 of the present invention; Figure 3 This is a small-scale igneous dike distribution map on the seismic variance profile in Embodiment 1 of the present invention; Figure 4 This is a small-scale igneous dike distribution map on the root mean square amplitude plane of the earthquake in Embodiment 1 of the present invention; Figure 5 This is an overlay diagram showing the distribution of small-scale igneous dikes with different seismic properties in Embodiment 1 of the present invention; Figure 6 This is a theoretical diagram of the dimensionless pressure and the double logarithmic curve of the dimensionless pressure integral derivative in Embodiment 1 of the present invention; Figure 7 This is a fitting diagram of actual data from well A32 in Embodiment 1 of the present invention; Figure 8 This is a correction diagram of a small-scale igneous dike in Embodiment 1 of the present invention (two solid lines and two scattered lines; the solid lines are theoretical curves, and the scattered lines are actual data; the upper line is the dimensionless pressure integral curve, and the lower line is the dimensionless pressure integral derivative curve). Figure 9 This is a distribution map of small-scale igneous dikes across the entire oilfield in Embodiment 1 of the present invention.
[0014] For those skilled in the art, other related figures can be obtained from the above figures without any creative effort. Detailed Implementation
[0015] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0016] Example 1 like Figure 1 As shown, a method for identifying small-scale igneous dikes based on seismic data and production data includes the following steps: S1. Based on the seismic data, geological data, and well logging data of the oilfield, clarify the spatiotemporal relationship of faults, magma, and sediments; Specifically, based on the geological background of the oilfield area, using the three-dimensional seismic and geological data of the oilfield, the periods of fault activity and igneous activity are divided. Based on the periods of fault activity and their extension scale, the periods and scale of igneous activity, as well as the time of stratigraphic deposition and oil and gas charging, the spatiotemporal relationship between faults, magma, and sediments is clarified. This embodiment selects the Bohai H oilfield, which is the first oilfield in the Bohai Sea to be developed in an igneous rock development area. The oilfield has strong tectonic activity, with multiple faults of varying scales and phases, and frequent volcanic eruptions. The volcanic activity is mainly divided into two phases. Based on the fault activity time and extension scale, the volcanic activity time and scale, and the stratigraphic deposition and oil and gas charging time, the spatiotemporal relationship of faults, magma, and sedimentation is as follows: After the formation of stratigraphic deposition within the oilfield, the early active faults connect downward to the magma chamber to form magma channels. Magma surges and intrudes into the strata (50 Ma~23 Ma). After the strata are cut, oil and gas are charged (10 Ma). Therefore, the magmatic action only affects the physical properties and connectivity of the sandstone reservoir and does not affect the later oil and gas charging process and degree.
[0017] S2. Using different attribute data of seismic data, small-scale igneous dikes are identified statically from both planar and longitudinal perspectives. Specifically, the following steps are included: S21. Finely identify small-scale igneous dikes on seismic profiles, delineate their locations, and form a distribution diagram of small-scale igneous dikes on seismic profiles. Figure 2 ); S22. Establish the variance volume attribute of the seismic data volume, perform fine identification of small-scale igneous dikes on the variance attribute profile, delineate the location of small-scale igneous dikes, and form the small-scale igneous dike distribution A of the variance profile. Figure 3 ); S23. Establish the root mean square amplitude attribute of the seismic data volume, and delineate the locations of small-scale igneous dikes on the root mean square attribute plane to form a planar small-scale igneous dike distribution B. Figure 4 ).
[0018] S3. Overlay the planar and longitudinal static identification results to classify the credibility of the small-scale igneous dikes identified by static identification. Specifically, the following steps are included: S31. Project the small-scale igneous dikes identified on the seismic profile and variance volume profile onto the plane position C; S32. Superimpose the small-scale igneous dikes identified by the three methods on a plane. Figure 5 The credibility of the rock walls is graded based on the degree of overlap depicted using different methods; the credibility levels are divided into four levels: Level 1, Level 2, Level 3, and Level 4. Since the root mean square amplitude is highly sensitive to lateral changes in amplitude, it can better reflect and identify changes in lithology and lithofacies, and thus locate dikes. Therefore, the reliability of igneous rocks identified by the root mean square amplitude attribute is the highest. Small-scale igneous dikes identified by all three methods at the same location are classified as Level 1. Small-scale igneous dikes identified by two methods at the same location, namely root mean square attribute and seismic profile or root mean square attribute and variance profile, are classified as Level 2. Small-scale igneous dikes identified by two methods at the same location, namely seismic profile and variance profile, are classified as Level 3. Small-scale igneous dikes identified by only one method are classified as Level 4 (Table 1).
[0019] Table 1: Classification Table of Igneous Rock Dikes S4. Extract the characteristics of oilfield well network and establish a theoretical chart of double logarithmic curves of pressure integral derivative under different closed ranges; Specifically, based on the geological and reservoir characteristics of the target oilfield, geological and reservoir parameters are obtained, well spacing and injection-production parameter characteristics are extracted, different small-scale igneous dike distances are set, and double logarithmic curves of pressure integral derivatives under different closure ranges are established using the formulas for calculating dimensionless pressure integrals and their derivatives. Sensitivity analysis is then conducted on the closure range of the igneous dikes.
[0020] The formula for calculating the dimensionless pressure integral is as follows: In the formula: This is a dimensionless pressure integral; Dimensionless pressure; The time for dimensionless mass equilibrium; The formula for calculating the dimensionless pressure integral derivative is as follows: In the formula: The derivative of the dimensionless pressure integral, This is a dimensionless pressure integral; The time for dimensionless mass equilibrium; The H oilfield has an average burial depth of 3035m, an average porosity of 25%, an average permeability of 145mD, and a comprehensive compressibility coefficient of 25×10⁻⁶. -4 / MPa, commissioning time 2019, average single-well production thickness 22m, injection-production well spacing 200-700m, average initial production capacity 119 cubic meters / day. Based on the above geological reservoir parameters, calculate the dimensionless pressure and dimensionless pressure integral derivative double logarithmic curve theoretical chart ( Figure 6 ).
[0021] S5. Fit the actual production data with the theoretical chart to obtain the fitting parameters and dynamically identify small-scale igneous dikes. The theoretical chart is a double logarithmic curve chart of pressure integral derivative under different closed ranges established in step S4. Specifically, based on the historical pressure and production data of a single well, the dimensionless pressure integral and the dimensionless pressure integral derivative are calculated. The dimensionless pressure and the dimensionless pressure integral derivative curves of a single well are plotted on a double logarithmic plot and fitted with the double logarithmic curve of the pressure integral derivative obtained in step S4, so that each set of curves can obtain a good fit as much as possible. The fitting parameters are obtained to determine the igneous rock closure range and dynamically identify small-scale igneous rock dikes.
[0022] Well A32 in the oilfield was put into production in 2019, with a production thickness of 32m, an average permeability of 110mD, and an initial production capacity of 185 cubic meters per day. After production began, injection and production efficiency was poor, energy replenishment was difficult, and production declined rapidly. Using historical pressure and production data of this well, the dimensionless pressure integral and its derivative were calculated and fitted with theoretical curves. Based on the fitted parameters, the distance of the small-scale igneous dikes surrounding well A32 from the well point was determined to be 110m. Figure 7 ).
[0023] S6. Based on the dynamic identification results, correct the small-scale igneous dikes identified in the static identification. Specifically, based on the dynamic identification results of igneous dikes, the location, quantity, and length of the igneous dikes are corrected to determine the final small-scale distribution of igneous dikes; Repeat step S5 to fit the data of 15 wells in areas with the development of Class I and II small-scale igneous dikes throughout the oilfield. Based on the fitting results, perform operations such as extending, splitting, and deleting the small-scale igneous dikes to determine the final distribution of the small-scale igneous dikes. Figure 8 ).
[0024] S7. Draw a small-scale distribution map of igneous dikes across the entire oilfield.
[0025] Specifically, based on the final small-scale igneous dike distribution determined in step S6, a small-scale dike distribution map is drawn within the target oilfield area by layer.
[0026] For oilfield H, based on the combined dynamic and static identification results, the distribution of each small-scale dike was precisely determined, and a small-scale dike distribution map was drawn within the target oilfield area. Figure 9 ).
[0027] The applicant declares that the above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.
Claims
1. A method for identifying small-scale igneous dyke based on seismic data and production data, characterized in that: The method comprises the following steps: S1, determining the space-time relationship of faults, magma and deposition according to oilfield seismic data, geological data and logging data; S2, identifying small-scale igneous dykes from plane and vertical statics respectively by using different attribute data of seismic data; S3, superimposing the plane and vertical identification results to classify the reliability of the small-scale igneous dykes identified by statics; S4, extracting the characteristics of the oilfield well pattern, and establishing theoretical graph of pressure integral derivative double logarithmic curve under different sealing ranges; S5, fitting the actual production data with the theoretical graph to obtain fitting parameters, and dynamically identifying the small-scale igneous dyke; S6, correcting the small-scale igneous dyke identified by statics according to the dynamic identification result; S7, drawing the distribution map of the small-scale igneous dyke in the whole oilfield.
2. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: The step S1 specifically comprises the following steps:
3. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: S1, determining the space-time relationship of faults, magma and deposition according to oilfield seismic data, geological data and logging data; The step S2 specifically comprises the following steps: S21, finely identifying the small-scale igneous dyke on the seismic profile, and drawing the position of the small-scale igneous dyke to form the distribution of the small-scale igneous dyke on the seismic profile; S22, establishing the variance body attribute of the seismic data body, finely identifying the small-scale igneous dyke on the variance attribute profile, and drawing the position of the small-scale igneous dyke to form the distribution of the small-scale igneous dyke on the variance profile; 4. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: S23, establishing the root mean square amplitude attribute of the seismic data body, and drawing the position of the small-scale igneous dyke on the root mean square attribute plane to form the distribution of the small-scale igneous dyke on the plane. The step S3 specifically comprises the following steps: S31, projecting the distribution of the small-scale igneous dyke on the seismic profile and the distribution of the small-scale igneous dyke on the variance profile into the distribution of the small-scale igneous dyke on the plane for superimposition; 5. The method for small-scale igneous dike identification based on seismic data and production data according to claim 4, characterized in that: S32, classifying the reliability according to the superimposition degree of the dyke drawn by different methods. The reliability is classified into four levels, i.e., first level, second level, third level and fourth level; The first level is the small-scale igneous dyke identified by the three methods at the same position; The second level is the small-scale igneous dyke identified by the root mean square attribute and the seismic profile or the root mean square attribute and the variance profile at the same position; The third level is the small-scale igneous dyke identified by the seismic profile and the variance profile at the same position; 6. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: The fourth level is the small-scale igneous dyke identified by only one method. The step S4 specifically comprises the following steps: According to the geological reservoir characteristics of the target oilfield, obtaining the geological reservoir parameters, extracting the well spacing and injection-production parameter characteristics, setting the distance of different small-scale igneous dykes, and establishing the pressure integral derivative double logarithmic curve graph under different sealing ranges by using the dimensionless pressure integral and dimensionless pressure integral derivative calculation formula to analyze the sensitivity of the sealing range of the igneous dyke.
7. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: The step S5 is specifically: according to the pressure and production history data of the single well, calculating the dimensionless pressure integral and the dimensionless pressure integral derivative, drawing the dimensionless pressure and the dimensionless pressure integral derivative curve of the single well on a double logarithmic graph, and fitting the pressure integral derivative double logarithmic curve obtained in the step S4, so that each group of curves can obtain a better fitting, obtaining the fitting parameters, determining the igneous rock sealing range, and dynamically identifying the small-scale igneous rock wall.
8. The method for small-scale igneous dike identification based on seismic data and production data according to claim 6 or 7, characterized in that: The dimensionless pressure integral calculation formula is: wherein: is the dimensionless pressure integral; is the dimensionless pressure; is the dimensionless material balance time; The dimensionless pressure integral derivative calculation formula is: where: is the dimensionless pressure integral derivative, is the dimensionless pressure integral; is the dimensionless material balance time.
9. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: The step S6 is specifically: according to the dynamic identification result of the igneous rock wall, correcting the position, quantity and length of the igneous rock wall, and determining the final small-scale igneous rock wall distribution.
10. The method for small-scale igneous dike identification based on seismic data and production data according to claim 1, characterized in that: The step S7 is specifically: according to the final small-scale igneous rock wall distribution determined in the step S6, drawing the small-scale igneous rock wall distribution graph in the target oilfield range in the stratigraphic position.