Method for identifying hidden trap boundary of ancient karst landform

Abstract

The invention discloses a karst ancient landform hidden trap boundary identification method, and belongs to the technical field of oil and gas field exploration and development. And in combination with karst development characteristics and oil and gas reservoir performance of the micro-landform unit, analyzing the relationship between the oil and gas yield and the landform, predicting a karst reservoir stratum, and further performing reservoir forming analysis to realize hidden trap boundary identification. According to the method, the hidden trap area is determined through combination of seismic data evaluation and stratum thickness prediction, the main development area of the carboniferous system stratum is determined through multiple amplitude attributes, then impedance characteristic expression is combined with multi-factor combination of forward modeling, seismic response, seismic inversion and physical property prediction, and finally high-quality reservoir stratum prediction is achieved. According to the karst ancient landform hidden trap boundary identification method, a multi-factor combination method is utilized, high-quality reservoir stratum prediction can be more accurately carried out, reservoir forming analysis and effective trap determination can be carried out, and finally hidden trap boundary identification is realized.

Description

Technical Field

[0001] The invention relates to a method for identifying a trap boundary, in particular to a method for identifying a hidden trap boundary of a karst paleo-geomorphology, and belongs to the technical field of oil and gas field exploration and development. Background Art

[0002] A trap refers to a geological place in the stratum that can prevent oil and gas from continuing to migrate, causing oil and gas to gather and form an oil and gas reservoir. A trap consists of three parts (reservoir: the main body of the trap, providing space for oil and gas storage; cap rock: an impermeable rock layer above the reservoir that prevents oil and gas from escaping; barrier: prevents oil and gas from continuing to migrate laterally and constitutes a barrier for accumulation). It can be a bending deformation of the cap rock itself, such as anticlines; or it can be another barrier, such as faults, lithology changes, etc. In short, a trap is an effective space that can capture dispersed hydrocarbons to form oil and gas accumulation, and has the ability to store oil and gas. Once a sufficient amount of oil and gas enters the trap, fills the trap or occupies part of the trap, an oil and gas reservoir can be formed.

[0003] Among them, hidden traps generally refer to traps that are difficult to identify using conventional interpretation and analysis methods, such as stratigraphic traps, lithologic traps, and low-amplitude structural traps. They are all caused by paleo-tectonic movements, erosion, hydrodynamic changes, and diagenesis, including stratigraphic updip pinch-outs, lenses, buried hills, reefs, and fractures. With the further deepening of oil and gas exploration, hidden traps are becoming increasingly important in oil and gas reserves.

[0004] At present, although a lot of research has been done on the identification of trap boundaries (such as: "CN104049275A Identification method and identification system for hidden trap boundaries in complex basin margin overstripping zones", "CN114442158A A method for identifying ultra-deep lithologic hidden oil and gas reservoirs", "Karst trap identification method and application of Longwangmiao Formation in Ziyang area, western Sichuan, Yi Yang et al., Science and Technology and Engineering, 2021-05-08", "Identification mode of hidden traps in irregular geological bodies and application of key technologies - taking fan traps as an example, Luo Qun et al., Lithologic Oil and Gas Reservoirs, 2013-12-15", etc.), there are few detailed descriptions of the combination of karst paleo-geomorphology and trap identification. There is also a lack of research on unit division. The methods used to consider the structural-sedimentary differentiation and geomorphological differences caused by regional tectonic movements are mainly the impression method and the residual thickness method. There are also methods that use error simulation methods and paleo-water depth recovery methods based on gamma-ray spectroscopy logging information to restore paleo-geomorphology. However, these methods for the division of paleokarst landforms mostly stop at secondary geomorphological units, namely karst highlands, karst slopes and karst depressions, etc. There is little work done on further micro-geomorphological characterization, which is not conducive to a more accurate description of the distribution law of karst reservoirs and cannot meet the prediction requirements for the distribution of local karst reservoirs. Summary of the invention

[0005] The present invention, based on the analysis of the influence of karst paleo-geomorphology, uses a combined seismic-geological method, utilizes the residual thickness method and the impression method to finely depict the karst paleo-geomorphological characteristics of the entire basin, and determines the distribution law of effective karst reservoirs in combination with drilling and production dynamic data. This can more accurately predict high-quality reservoirs, and simultaneously analyze the formation of reservoirs and determine effective closures, and ultimately realize the identification of hidden closure boundaries, in order to provide an effective basis for the exploration selection and well site deployment of karst reservoirs.

[0006] In order to achieve the above technical objectives, the following technical solutions are proposed: The method for identifying the boundary of hidden traps in karst paleo-geomorphology includes the following steps: S1: Predict and identify hidden trap areas based on seismic data evaluation and formation thickness; Classify the seismic data, and then evaluate the quality of the seismic data of the key layers, where the quality of the seismic data includes the reliability of the reflection axis; Combining the seismic forward model and reservoir seismic response characteristics, the formation thickness is qualitatively predicted according to the amplitude, and then the hidden trap area is determined; S2: Analyze the relationship between oil and gas production and landform by obtaining the karst development characteristics and oil and gas reservoir performance of micro-geomorphological units; On the basis of step S1, geomorphic identification factors are added to divide 8 third-level geomorphic units (including: karst highland peak clusters, karst gullies, karst slope residual hills, sinkholes, valleys, underground rivers, karst depressions and depression residual hills) to identify paleo-geomorphic forms; with reference to drilling lithology, drilling physical properties and drilling gas content under paleo-geomorphic forms, the landforms with rich oil and gas production are screened out; S3: Prediction of karst reservoirs by combining multiple factors; Predict high-quality reservoirs based on impedance characteristics, forward modeling, seismic response, seismic inversion and physical property prediction; S4: Reservoir analysis and determination of effective traps.

[0007] Furthermore, the multi-factor combined prediction of karst reservoir in step S3 includes analyzing: Impedance characteristics of high-quality reservoirs: Wave impedance has a certain ability to distinguish between gas-producing wells and dry wells. The higher the production capacity of a gas-producing well, the lower the impedance, the better the physical properties, and the greater the degree of distinction from dry wells; Forward simulation: The difference in physical properties of Carboniferous reservoirs will cause amplitude changes. The better the reservoir, the smaller the amplitude value. The thickness of Carboniferous reservoirs will cause the amplitude to weaken significantly. The thicker the reservoir, the stronger the amplitude. Seismic response: The development of high-quality reservoirs in the Carboniferous will lead to the weakening of strong wave peaks; Seismic inversion: Different sedimentary microfacies and reservoir characteristics affect seismic waveforms, so reservoirs are predicted based on waveform classification methods; Physical property prediction: Through drilling verification, it is found that the area with the best physical properties has weak amplitude and low impedance, while the area with poor physical properties has strong amplitude and high impedance.

[0008] Furthermore, the step S3 extracts wave impedance attributes to preliminarily clarify the distribution of relatively high-quality reservoirs; and realizes karst reservoir prediction by combining multiple factors; The impedance characteristics of the high-quality reservoir are mainly characterized by high acoustic waves, low density, strong, medium and weak seismic response characteristics and low impedance characteristics.

[0009] Furthermore, before the multi-factor joint karst reservoir prediction in step S3 is started, the stratum distribution prediction is performed, that is, the main development areas of the Carboniferous strata are clarified by using a variety of amplitude attributes.

[0010] The beneficial technical effects brought about by adopting this technical solution are: 1. The present invention combines the karst development characteristics of micro-geomorphic units and the oil and gas reservoir performance, analyzes the relationship between oil and gas production and landforms, predicts karst reservoirs, and further performs reservoir formation analysis to identify the boundaries of hidden traps; and determines the hidden trap area through seismic data evaluation combined with formation thickness prediction, clarifies the main development area of ​​the Carboniferous strata through a variety of amplitude attributes, and then combines the impedance characteristic performance with forward simulation, seismic response, seismic inversion, physical property prediction and other factors to more accurately predict high-quality reservoirs; Second, karstification is a prerequisite for reservoir formation, and favorable karst paleo-geomorphology is more conducive to the development of reservoirs; high-quality reservoirs are the basis for the development of traps, and lithology and structure jointly control the scope of traps. Through the above ideas, the present invention can more accurately predict high-quality reservoirs, analyze reservoir formation and determine effective traps, and ultimately realize the identification of hidden trap boundaries. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a seismic data quality evaluation diagram in the present invention; Figure 2 This is the earthquake forward model diagram in the present invention; Figure 3 It is the calibration diagram of the well logging curve in the present invention; Figure 4 It is the earthquake favorable area prediction map in the present invention; DETAILED DESCRIPTION

[0012] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0013] Example 1 This embodiment provides: a method for identifying hidden trap boundaries of karst paleo-geomorphology, comprising the following steps: S1: Predict and identify hidden trap areas based on seismic data evaluation and formation thickness; Classify the seismic data, and then evaluate the quality of the seismic data of key layers (such as Figure 1 As shown in Figure 2), the quality of seismic data includes the reliability of the reflection axis; Combined with the earthquake forward model (such as Figure 2 The thickness of the formation is qualitatively predicted based on the amplitude of the seismic response characteristics of the reservoir, and the hidden trap area is determined; S2: Analyze the relationship between oil and gas production and landform by obtaining the karst development characteristics and oil and gas reservoir performance of micro-geomorphological units; Add geomorphic identification factors, further divide into 8 third-level geomorphic units (including: karst highland peak clusters, karst gullies, karst slope residual hills, sinkholes, valleys, underground rivers, karst depressions and depression residual hills), identify paleo-geomorphic forms; use drilling lithology, drilling physical properties and drilling gas content under paleo-geomorphic forms as references to screen out landforms with rich oil and gas production; S3: Prediction of karst reservoirs by combining multiple factors; First, the stratigraphic distribution is predicted, that is, the main development areas of the Carboniferous strata are determined using a variety of amplitude attributes; Then, the impedance characteristics are combined with forward modeling, seismic response, seismic inversion and physical property prediction to predict high-quality reservoirs; The analyses involved include: Impedance characteristics of high-quality reservoirs: Wave impedance has the ability to distinguish between gas-producing wells and dry wells. The higher the production capacity of a gas-producing well, the lower the impedance, the better the physical properties, and the greater the degree of distinction from dry wells; Forward simulation: The difference in physical properties of Carboniferous reservoirs will cause amplitude changes. The better the reservoir, the smaller the amplitude value. The thickness of Carboniferous reservoirs will cause the amplitude to weaken significantly. The thicker the reservoir, the stronger the amplitude. Seismic response: The high-quality reservoirs developed in the Carboniferous will lead to the weakening of strong wave peaks; Seismic inversion: Different sedimentary microfacies and reservoir characteristics affect seismic waveforms, so reservoirs are predicted based on waveform classification methods; Physical property prediction: Drilling verifies that the weak amplitude impedance is low in areas with good physical properties, and that the strong amplitude impedance is high in areas with poor physical properties; Among them, by extracting the wave impedance attributes, the distribution of relatively high-quality reservoirs is preliminarily clarified; combining multiple factors to achieve karst reservoir prediction; among them, the impedance characteristics of high-quality reservoirs are high acoustic waves and low density, and the seismic response characteristics of high-quality reservoirs are strong, medium, weak and low impedance; S4: Reservoir analysis and determination of effective traps.

[0014] Example 2 Based on Example 1, this example discusses the relationship between physical properties and amplitude to further illustrate the technical solution.

[0015] like Figure 3 As shown, it can be seen that the relationship between physical properties and amplitude is: the better the physical properties, the weaker the amplitude; At the same time, the forward modeling results show that the physical property differences of the Carboniferous reservoir will cause the amplitude to change. The better the reservoir, the smaller the amplitude value. The forward modeling results also show that the thickness of the Carboniferous reservoir will cause the amplitude to weaken significantly. The thicker the reservoir, the stronger the amplitude.

[0016] In summary, the change of reservoir thickness has a great influence on the amplitude; in addition, it also shows that the change of reservoir physical properties is not likely to cause the special reflection phenomena such as obvious pull-down or pull-up of various phase axes of the Carboniferous in the work area and blank reflection. Therefore, the fluctuation of the formation interface or the development of a new type of reservoir (fracture-cavity or high-porosity reservoir with a velocity lower than that of conventional reservoirs) should be the main reason for the special reflection phenomenon.

[0017] Example 3 Based on Example 1, this example discusses the prediction of stratum distribution to further illustrate the technical solution.

[0018] To predict the stratigraphic distribution, we use a variety of amplitude attributes to identify the main development areas of the Carboniferous strata, such as Figure 4 As shown, The stratigraphic erosion zone is mainly located in the west and north of the three-dimensional study area. There is an obvious amplitude mutation in the west of the study area, which is an erosion zone; the amplitude changes from strong to weak from south to north in the study area, indicating that the stratigraphic thickness changes from thick to thin.

[0019] Example 4 Based on Example 1, this example discusses the earthquake response characteristics to further illustrate the technical solution.

[0020] Relatively low impedance, strong to medium to weak amplitudes against a high impedance background; In order to verify the influence of high-quality reservoirs in the Carboniferous strata on seismic response, drilling verification was carried out; from the forward modeling results, the development of high-quality reservoirs in the Carboniferous will lead to the weakening of strong peaks, indicating that the prediction mode of finding the weak among the strong can be adopted to predict high-quality reservoirs.

[0021] Example 5 On the basis of Example 1, this example discusses the clarification of the main development zones of the Carboniferous strata to further illustrate the technical solution.

[0022] Optimization of major development areas: Through the extraction of wave impedance attributes, the distribution of relatively high-quality reservoirs was preliminarily clarified. Reservoirs are well developed in the western area with few wells, and the western part of the Wubaiti gas field is the most typical, which has great exploration and evaluation potential.

[0023] Example 6 Based on Example 1, this example discusses the relationship between the formation morphology and the phase and waveform to further illustrate the technical solution.

[0024] When the Carboniferous is the peak and is relatively high in seismic reflection characteristics, the reflection event will be lifted, and at the same time, its lower phase amplitude will be enhanced and lifted; conversely, when the Carboniferous strata are thinner, the event will be pulled down, and its lower phase amplitude will be weakened accordingly. It is interpreted as the peak clusters, residual hills and shallow depressions of the karst highlands.

[0025] When the reservoir is developed in the upper part of the rock formation, it will cause the phase axis to pull down. The greater the reservoir depth, the more obvious the pull-down; When the reservoir is developed in the middle of the rock formation, there will be a slight pull-down and weakened amplitude; When the reservoir is developed in the lower part of the rock formation, only the amplitude weakening phenomenon will occur.

[0026] The prediction results show that the Carboniferous reservoirs in Wubaiti are differentially distributed and may develop underground rivers and sinkholes.

[0027] The forward modeling results show that different sedimentary microfacies and reservoir characteristics have an impact on the seismic waveform, so the reservoir is predicted based on the waveform classification method.

Claims

1. A method for identifying hidden trap boundaries in karst paleo-geomorphology, characterized in that: The steps include: S1: Predict and identify hidden trap areas based on seismic data evaluation and formation thickness; Classify the seismic data, and then evaluate the quality of the seismic data in key formations; Combined with the seismic forward model and reservoir seismic response characteristics, the formation thickness is qualitatively predicted according to the amplitude and the hidden trap area is determined; S2: Analyze the relationship between oil and gas production and landform by obtaining the karst development characteristics and oil and gas reservoir performance of micro-geomorphological units; Add geomorphic identification factors, divide the three-level geomorphic units, and identify the paleo-geomorphic forms; use the drilling lithology, drilling physical properties, and drilling gas content under the paleo-geomorphic forms as a reference to screen out the landforms with rich oil and gas production; S3: Prediction of karst reservoirs by combining multiple factors; Combine impedance characteristics with forward modeling, seismic response, seismic inversion and physical property prediction to predict high-quality reservoirs; S4: Reservoir analysis and determination of effective traps.

2. The method for identifying hidden trap boundaries of karst paleo-geomorphology according to claim 1, characterized in that: In step S1 , the seismic data quality includes the reliability of the reflection axis.

3. The method for identifying hidden trap boundaries of karst paleo-geomorphology according to claim 1 or 2, characterized in that: In step S2, the third-level geomorphic units include karst highland peaks, karst gullies, karst slope residual hills, sinkholes, valleys, underground rivers, karst depressions and depression residual hills.

4. The method for identifying hidden trap boundaries of karst paleo-geomorphology according to claim 3, characterized in that: In step S3, multiple factors are combined to predict karst reservoirs, and the analysis involved includes: The impedance characteristics of high-quality reservoirs. Wave impedance has the ability to distinguish between gas-producing wells and dry wells. The higher the production capacity of a gas-producing well, the lower the impedance, the better the physical properties, and the greater the degree of distinction from dry wells. Forward simulation shows that the difference in physical properties of Carboniferous reservoirs will cause amplitude changes. The better the reservoir, the smaller the amplitude value. The thickness of Carboniferous reservoirs will cause the amplitude to weaken significantly. The thicker the reservoir, the stronger the amplitude. In terms of seismic response, the high-quality reservoirs developed in the Carboniferous will lead to the weakening of strong wave peaks; Seismic inversion, different sedimentary microfacies and reservoir characteristics affect the seismic waveform, so the reservoir is predicted based on waveform classification methods; Physical property prediction verifies through drilling that the amplitude weak impedance of the area with good physical properties is low, and that the amplitude strong impedance of the area with poor physical properties is high.

5. The method for identifying hidden trap boundaries of karst paleo-geomorphology according to claim 4, characterized in that: In step S3, it also includes: By extracting wave impedance attributes, the distribution of relatively high-quality reservoirs is preliminarily clarified; combining multiple factors to achieve karst reservoir prediction; among them, the impedance characteristics of high-quality reservoirs are manifested as high acoustic waves and low density, and the seismic response characteristics of high-quality reservoirs are manifested as strong, medium, weak and low impedance.

6. The method for identifying hidden trap boundaries of karst paleo-geomorphology according to claim 5, characterized in that: In step S3, before the prediction of karst reservoirs is carried out by combining multiple factors, the stratum distribution prediction is carried out, that is, the main development areas of the Carboniferous strata are clarified by using multiple amplitude attributes.

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