A method for identifying a lithologic trap of a glutenite body

Abstract

The present application belongs to the technical field of oil exploration and development, and particularly relates to a method for identifying sandstone and conglomerate lithologic traps. In the presence of complex sedimentary conditions, the present application first divides the sandstone and conglomerate into sedimentary stages by comprehensively utilizing seismic data and core, well logging and mud logging data of the measured well in the work area, then analyzes the seismic response characteristics of the positions of fan root, fan middle and fan end, and interprets the sandstone and conglomerate seismic facies based on the seismic data to delineate the seismic facies distribution range, and further determines the sandstone and conglomerate lithologic sensitive parameters and the relationship between the sandstone and conglomerate lithologic sensitive parameters and reservoir porosity, so as to delineate the sweet spot range, and superimpose the seismic facies and sweet spot range with the structure map to delineate the trap range. The whole process comprehensively utilizes different data, including seismic, core, well logging and mud logging data, establishes a trap identification method suitable for sandstone and conglomerate, and improves the sandstone and conglomerate fan trap identification accuracy, thereby laying a foundation for efficient exploration and development of sandstone and conglomerate oil and gas reservoirs.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration and development technology, specifically relating to a method for identifying lithological traps in conglomerate bodies. Background Technology

[0002] Traps are suitable locations for the accumulation of oil and gas, forming oil and gas reservoirs. Lithological traps in sandstone and conglomerate bodies are an important type of trap, and identifying sandstone and conglomerate traps is an effective way to find oil and gas reservoirs. During the stratigraphic deposition process in the steep slope zone of continental rift basins, the proximity of the source material and the steep slope lead to rapid sediment accumulation, poor sorting, and rapid changes in reservoir properties, which easily form lithological traps.

[0003] Currently, scholars have conducted extensive research on the identification of sedimentary facies zones in conglomerate fans. For example, Chinese invention patent application CN111399055A discloses a method for describing the facies zones of conglomerate bodies based on velocity dispersion factors. This method, after completing the interpretation of the conglomerate body's phases, extracts velocity dispersion attributes for each phase and then uses conventional seismic attributes as an aid to complete the description of favorable reservoir phase facies zones in conglomerate bodies under complex sedimentary environments. Chinese invention patent application CN111175819A discloses a method for finely delineating sedimentary facies zones in conglomerate fans with multi-level well-seismic constraints. This method uses seismic facies as the first-level constraint condition and establishes a quantitative well-logging identification template by analyzing the lithology and well-logging curves of subfacies and microfacies. Simultaneously, through well-logging cross-plot analysis, it clarifies the well-logging sensitivity curves for different microfacies. Furthermore, through data discretization and using variograms as a technical means, numerical simulations are conducted under a geological model with fine phase delineation and tectonic phase modeling, achieving fine delineation of sedimentary facies zones in conglomerate sedimentary bodies through well-seismic numerical simulation. These methods are mainly for identifying the extent of sandstone and conglomerate facies zones, but they do not go further to identify the effective trap extent.

[0004] Conglomerate bodies differ from other rock bodies. In specific oil exploration work, due to the superposition of conglomerate bodies from different periods, the longitudinal and lateral facies zones change rapidly. Even within the same facies zone, the reservoir properties at different locations are not entirely the same. For lithological traps formed under such complex sedimentary conditions, the existing methods for identifying traps in other rock bodies are not applicable to the identification of lithological traps in conglomerate bodies, and accurate identification of lithological traps in conglomerate bodies cannot be achieved. Summary of the Invention

[0005] The purpose of this invention is to provide a method for identifying lithological traps in conglomerate bodies, thereby solving the problem that existing technologies cannot accurately identify lithological traps in conglomerate bodies.

[0006] To solve the above-mentioned technical problems, the technical solution provided by this invention and the corresponding beneficial effects of the technical solution are as follows:

[0007] This invention provides a method for identifying lithological traps in conglomerate bodies, comprising the following steps:

[0008] 1) Obtain post-stack seismic profile data of the work area, as well as well logging, well logging and core data of the drilled wells in the work area;

[0009] 2) Based on the logging, well logging, and core data of the drilled wells, determine the single-well facies characteristics of the fan root, fan middle, and fan tip of each drilled conglomerate body, and classify the sedimentary cycles; conduct well-to-well correlation of each drilled well to establish a well-to-well facies model of the conglomerate body, and classify the sedimentary periods of the conglomerate body in the work area according to the sedimentary cycles; obtain the synthetic seismic record of each drilled well based on the logging data, and use the synthetic seismic record to calibrate the conglomerate body;

[0010] 3) Extract seismic profile data from all drilled wells, and map the single-well facies characteristics and sedimentary cycles of the conglomerate fan root, fan middle, and fan end in step 2) onto the seismic profile data. Analyze the seismic response characteristics of the fan root, fan middle, and fan end positions on the seismic profile data of the conglomerate fan, and establish seismic facies identification standards for the conglomerate fan in the work area.

[0011] 4) Based on the established seismic facies identification criteria, the seismic facies of sandstone and conglomerate bodies are interpreted on the post-stack seismic profile data of the work area, the seismic facies distribution range is delineated, and the envelope positions of the fan roots, fan middle and fan ends of each phase are determined to identify all the fan bodies included in each phase.

[0012] 5) Utilize well logging data from drilled wells within the work area to conduct rock physics cross-analysis, determine conglomerate sensitivity parameters and their relationship with reservoir porosity, and obtain the value ranges of conglomerate sensitivity parameters and porosity that meet reservoir conditions; perform conglomerate sensitivity parameter inversion calculations for each sector included in each phase, use the obtained conglomerate sensitivity parameter value ranges as constraints to calculate the effective reservoir thickness, and delineate areas where the reservoir thickness exceeds the set reservoir thickness threshold; perform porosity inversion for each sector included in each phase, delineate areas where the porosity is within the porosity value range; overlay the areas where the reservoir thickness exceeds the predicted set reservoir thickness with the areas where the porosity is within the porosity value range to delineate the sweet spot range;

[0013] 6) Overlay the delineated seismic phases and sweet spot areas with the structural map of the work area to delineate the enclosed area.

[0014] Its beneficial effects are as follows: Facing complex sedimentary conditions, this invention first integrates seismic data from the work area with core, well, and logging data from existing wells to classify the sedimentary stages of the conglomerate body. Then, it analyzes the seismic response characteristics of the fan root, fan middle, and fan tip locations. Based on the different seismic response characteristics of each facies zone, the seismic data is interpreted as a seismic facies of the conglomerate body, delineating the distribution range of favorable facies zones in the fan middle. On this basis, by determining the sensitive parameters of conglomerate lithology and the relationship between these parameters and reservoir porosity, the sweet spot area is delineated. Finally, the delineated facies zones and sweet spot areas in the fan middle are overlaid with the structural map of the work area to delineate the trap area. The entire process comprehensively utilizes various data, including seismic, core, well logging, and well logging data. Through sedimentary phase division, favorable facies zone delineation, sand body prediction, sweet spot identification, and hierarchical constraints, a trap identification method suitable for sandstone and conglomerate bodies was established. This improved the trap identification accuracy of sandstone and conglomerate fan bodies, and has important guiding significance for the exploration of sandstone and conglomerate fan bodies in the work area. It lays the foundation for the efficient exploration and development of oil and gas reservoirs in sandstone and conglomerate bodies and has high practical application value.

[0015] Furthermore, in step 1), the post-stack seismic profile data also needs to be smoothed and filtered to remove noise.

[0016] Its beneficial effects are: smoothing and filtering the post-stack seismic profile data can improve the signal-to-noise ratio of the seismic profile data, laying the foundation for improving the accuracy of trap identification.

[0017] Furthermore, the sedimentation periods divided in step 2) include three periods.

[0018] Furthermore, the well logging data used to obtain the synthetic seismic record in step 2) includes sonic logging curves and density logging curves.

[0019] Its beneficial effects are: synthetic seismic records can be accurately calculated using sonic logging data and density logging curves, laying the foundation for subsequent precise calibration of sandstone and conglomerate bodies.

[0020] Furthermore, the seismic response characteristics at the root of the fan include: blank reflection with low-frequency characteristics; the seismic response characteristics in the middle of the fan include: medium-to-strong amplitude reflection characteristics, medium-to-long continuous phase axis with medium-frequency characteristics; and the seismic response characteristics at the tip of the fan include: medium-to-weak amplitude reflection characteristics, medium-to-short continuous phase axis, obvious bifurcation and merging with higher frequencies.

[0021] Its beneficial effects are: based on the above principles, the root, middle and end of the fan can be accurately distinguished, so as to establish an accurate seismic facies identification standard for sand and conglomerate bodies in the work area.

[0022] Further, in step 4), the envelope positions of the fan root, fan middle and fan end of each period are determined on the plane.

[0023] Its beneficial effect is that the envelope positions of the fan root, fan middle and fan end of each period can be clearly distinguished in the plane.

[0024] Furthermore, the sandstone and conglomerate sensitive parameter mentioned in step 5) is the longitudinal wave impedance, which is obtained by cross-analysis of the natural gamma and longitudinal wave impedance of the wells already drilled in the work area.

[0025] Its beneficial effect is that the longitudinal wave impedance can be used to accurately distinguish lithology.

[0026] Furthermore, the longitudinal wave impedance ranges from 11500 to 13500 g / cm. 3 *m / s, porosity range is greater than 6%.

[0027] Furthermore, in step 5), the reservoir thickness threshold is set to 10m. Attached Figure Description

[0028] Figure 1 This is an overall flowchart of the method for identifying lithological traps in conglomerate bodies according to the present invention;

[0029] Figure 2 This is a seismic profile of the post-stack three-dimensional pure wave seismic data (S1) after filtering and smoothing processing according to the present invention;

[0030] Figure 3(a) is a core diagram of a typical fan root in well A1;

[0031] Figure 3(b) is a core diagram of a typical fan in well A1;

[0032] Figure 3(c) is a core image of a typical fan end of well A1;

[0033] Figure 4(a) is a logging phase diagram of a typical fan root of well A1;

[0034] Figure 4(b) is a logging phase diagram of a typical sector in well A1;

[0035] Figure 4(c) is a logging phase diagram of a typical sector of well A1;

[0036] Figure 5 This is a sedimentary microfacies diagram of well A1;

[0037] Figure 6 This is a well facies diagram connecting wells A1, A2, and A3;

[0038] Figure 7 This is the calibration map of the synthetic record of well A1;

[0039] Figure 8 This is the calibration diagram for wells A1, A2, and A3.

[0040] Figure 9 This is a seismic response characteristic analysis diagram of the A1, A2, and A3 well profiles;

[0041] Figure 10 These are seismic facies interpretation profiles of the root, middle, and tip of a conglomerate fan.

[0042] Figure 11 This is a map showing the extent of the fan root, fan middle, and fan tip of the Phase II sandstone and conglomerate body;

[0043] Figure 12 It is a plot of the intersection of longitudinal wave impedance and natural gamma;

[0044] Figure 13 It is a graph showing the intersection of measured porosity and longitudinal wave impedance;

[0045] Figure 14 This is the impedance inversion profile of well B1;

[0046] Figure 15 It is the second phase sector H2Ⅱ10 1 Small-layer wave impedance inversion planar diagram;

[0047] Figure 16 It is the second phase sector H2Ⅱ10 1 Predicted layer thickness;

[0048] Figure 17 It is the second phase sector H2Ⅱ10 1 Predicted porosity of small layers;

[0049] Figure 18 It is the second phase sector H2Ⅱ10 1 Comprehensive evaluation diagram of small-scale traps. Detailed Implementation

[0050] This invention proposes a method for identifying lithological traps in sandstone and conglomerate bodies, utilizing existing seismic, well logging, and production data. The invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0051] Example of a method for identifying lithological traps in conglomerate bodies:

[0052] This embodiment uses work area A in a rift basin as an example for illustration. The 3D seismic data area of ​​this work area is approximately 100 km². 2 Six exploratory wells have been drilled: A1, A2, A3, B1, B2, and B3. Figure 1 As shown, the entire process of identifying lithological traps in conglomerate bodies is as follows:

[0053] Step 1: Obtain the post-stack 3D pure wave seismic data volume (denoted as S1) of work area A, as well as the logging, well logging and core data of six exploration wells A1, A2, A3, B1, B2 and B3.

[0054] Step two: Filter and smooth the post-stack 3D pure wave seismic data volume S1 of work area A to remove noise and improve the signal-to-noise ratio of the seismic data, resulting in the filtered seismic data volume, as shown below. Figure 2 As shown, it is denoted as S2.

[0055] Step 3: Based on the core data, logging data, and well logging data from the drilled wells, determine the single-well facies characteristics of the fan root, fan middle, and fan tip of the conglomerate body, and classify the sedimentary cycles.

[0056] The following explanation uses well A1 as an example. In the core images of well A1, as shown in Figure 3(a), the typical fan-root facies zone is characterized by mixed accumulation and gravel development; as shown in Figure 3(b), the fan-middle facies zone is dominated by fine to medium gravel, with good roundness and good sorting; as shown in Figure 3(c), the fan-end facies zone is dominated by dark mudstone and silty mudstone, with local thin sandstone stripes. For well A1, as shown in Figure 4(a), the typical fan-root logging facies is characterized by thick layers of sandstone and conglomerate, severely toothed GR curves (natural gamma curves), poor sorting, and mixed accumulation; as shown in Figure 4(b), the typical fan-middle logging facies is dominated by fine sandstone and gravelly fine sandstone, with full GR and SP curves (spontaneous potential curves), obvious mirror characteristics, good sorting, and relatively good reservoir conditions; as shown in Figure 4(c), the typical fan-end logging facies is dominated by mudstone, with local thin siltstone layers. Based on the comprehensive analysis of core facies, logging facies, and well logging lithology data, the sedimentary cycles of well A1 are classified, such as... Figure 5 As shown. The above process was repeated for wells A2, A3, B1, B2, and B3 to complete the single-well facies interpretation and sedimentary cycle classification of wells A2, A3, B1, B2, and B3, respectively.

[0057] Step four: Following the provenance direction from south to north, select wells A1, A2, and A3 to establish a well-connected facies model of the conglomerate body through well-to-well correlation. Based on sedimentary cycles, preliminarily divide the sedimentary deposition of the conglomerate body in the work area into three major phases, such as... Figure 6 As shown: Phase I is H2Ⅲ, Phase II is H2Ⅱ, and Phase III is H2Ⅰ (H2Ⅰ, H2Ⅱ, and H2Ⅲ are the names of the Paleogene Hetaoyuan Formation sandstone groups in the work area).

[0058] Step 5: Using the sonic and density logging curves from the drilled wells, create a single-well synthetic seismic record and finely calibrate the sandstone and conglomerate body.

[0059] The following explanation uses well A1 as an example. A synthetic log is calculated using the sonic and density logging curves of well A1. This synthetic log is then compared and calibrated with the seismic traces near the well to complete the fine calibration of the sandstone and conglomerate body. The fine calibration results are as follows: Figure 7 As shown. The same operation was performed to complete the calibration of the synthetic records for wells A2, A3, B1, B2, and B3.

[0060] Step Six: Extract the seismic profiles of the interconnected wells. Map the single-well facies characteristics and sedimentary cycles of the sandstone and conglomerate fan root, fan middle, and fan end from Step Three onto the interconnected seismic profiles. Taking the interconnected profiles of wells A1, A2, and A3 as an example... Figure 8 As shown, the seismic response characteristics at the root, middle, and tip of the fan on the well-connected seismic profile are analyzed. Figure 9 As shown, a seismic facies identification standard for sandstone and conglomerate in this work area is established.

[0061] like Figure 9 The seismic response at the root of the fan is characterized by blank reflection and low frequency (dominant frequency 15Hz); the entire fan exhibits medium-to-strong amplitude reflection characteristics, with a long and continuous phase axis and a medium frequency (dominant frequency 25Hz); the fan tip shows medium-to-weak amplitude reflection characteristics, with a short and continuous phase axis, obvious bifurcation and merging, and a higher frequency (dominant frequency 30Hz).

[0062] Step 7: On the seismic profile of the filtered seismic data volume S2, perform seismic facies interpretation of sandstone and conglomerate bodies at equal intervals (8 traces per interval), and draw the envelope positions of the fan roots, fan middle, and fan ends for each period, as shown below. Figure 10 As shown.

[0063] Step 8: Delineate the fan root, fan middle, and fan end ranges for each period on the plane.

[0064] The following description uses the Phase II conglomerate fan as an example. Based on the locations of the envelope lines at the bottom interface of the Phase II fan root, middle, and tip as interpreted from the seismic profiles in Step Seven, the ranges of the fan root, middle, and tip are delineated on the plane. The ranges of the other two phases of conglomerate fans are then delineated using the same method. Ultimately, four conglomerate fans are delineated, from west to east: Fan ①, Fan ②, Fan ③, and Fan ④. Figure 11 As shown.

[0065] Step nine involves identifying favorable facies zones within the reservoir fan, determining lithologically sensitive parameters through rock physics cross-analysis, conducting seismic inversion prediction, quantitatively predicting reservoir thickness and porosity, and characterizing the sweet spot area of ​​the reservoir.

[0066] The following uses sector number ①, period II, H2Ⅱ10 1 The process for other sectors is the same, and mainly consists of the following three steps:

[0067] 1. Conduct cross-analysis of rock physics to clarify lithological sensitive parameters and their relationship with reservoir physical properties and porosity.

[0068] Through the cross-analysis of natural gamma and P-wave impedance of drilled wells in the work area, when the P-wave impedance value is greater than 11500 g / cm 3 When the velocity is *m / s and the natural gamma is less than 110 API, the lithology is mostly sandstone or gravelly sandstone, and the reservoir exhibits medium to high impedance characteristics, such as... Figure 12As shown. Therefore, P-wave impedance can distinguish lithology in this work area. Based on this, by combining measured porosity and P-wave impedance, it was determined that under the condition of a lower porosity limit of 6%, the P-wave impedance range is 11500–13500 g / cm³. 3 *m / s, such as Figure 13 As shown.

[0069] 2. Conduct longitudinal wave impedance inversion and porosity inversion to quantitatively predict reservoir thickness and porosity.

[0070] Wave impedance inversion calculations were performed on sector ① in phase II, yielding wave impedance data volume S3, as follows: Figure 14 As shown; extract H2Ⅱ10 from the S3 data volume. 1 By slicing the small layer along the layer, the wave impedance inversion plane diagram of that layer is obtained, as shown below. Figure 15 As shown; the longitudinal wave impedance range of 11500-13500 g / cm² obtained from the rock physics intersection analysis in step 1 is given. 3 *m / s is a constraint condition; calculate H2Ⅱ10. 1 The thickness of the small reservoir layer is used to obtain an effective reservoir thickness prediction map, such as... Figure 16 As shown, regions with reservoir thicknesses greater than 10 m are delineated. Then, the physical property distribution characteristics of this sub-layer are predicted through porosity inversion, such as... Figure 17 As shown, the region with a porosity greater than 6% is delineated. The sweet spot region is delineated by superimposing the reservoir thickness and porosity.

[0071] Step 10: Delineate the lithological trap area.

[0072] Overlay the seismic facies distribution range obtained in step eight and the sweet spot area range obtained in step nine with the structural map of the work area, such as... Figure 18 As shown, the enclosed area is delineated, and a table of enclosed elements is created, as shown in Table 1.

[0073] Table 1

[0074]

Claims

1. A method for identifying lithological traps in conglomerate bodies, characterized in that, Includes the following steps: 1) Obtain post-stack seismic profile data of the work area, as well as well logging, well logging and core data of the drilled wells in the work area; 2) Based on the logging, well logging, and core data of the drilled wells, determine the single-well facies characteristics of the fan root, fan middle, and fan tip of each drilled conglomerate body, and classify the sedimentary cycles; conduct well-to-well correlation of each drilled well to establish a well-to-well facies model of the conglomerate body, and classify the sedimentary periods of the conglomerate body in the work area according to the sedimentary cycles; obtain the synthetic seismic record of each drilled well based on the logging data, and use the synthetic seismic record to calibrate the conglomerate body; 3) Extract seismic profile data from all drilled wells, and map the single-well facies characteristics and sedimentary cycles of the conglomerate fan root, fan middle, and fan end in step 2) onto the seismic profile data. Analyze the seismic response characteristics of the fan root, fan middle, and fan end positions on the seismic profile data of the conglomerate fan, and establish seismic facies identification standards for the conglomerate fan in the work area. 4) Based on the established seismic facies identification criteria, the seismic facies of sandstone and conglomerate bodies are interpreted on the post-stack seismic profile data of the work area, the seismic facies distribution range is delineated, and the envelope positions of the fan roots, fan middle and fan ends of each phase are determined to identify all the fan bodies included in each phase. 5) Utilize well logging data from drilled wells within the work area to conduct rock physics cross-analysis, determine conglomerate sensitivity parameters and their relationship with reservoir porosity, and obtain the value ranges of conglomerate sensitivity parameters and porosity that meet reservoir conditions; perform conglomerate sensitivity parameter inversion calculations for each sector included in each phase, use the obtained conglomerate sensitivity parameter value ranges as constraints to calculate the effective reservoir thickness, and delineate areas where the reservoir thickness exceeds the set reservoir thickness threshold; perform porosity inversion for each sector included in each phase, delineate areas where the porosity is within the porosity value range; overlay the areas where the reservoir thickness exceeds the predicted set reservoir thickness with the areas where the porosity is within the porosity value range to delineate the sweet spot range; 6) Overlay the delineated seismic phases and sweet spot areas with the structural map of the work area to delineate the enclosed area.

2. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, In step 1), the post-stack seismic profile data also needs to be smoothed and filtered to remove noise.

3. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, The sedimentation periods divided in step 2) include three periods.

4. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, The well logging data used to obtain the synthetic seismic record in step 2) includes sonic logging curves and density logging curves.

5. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, The seismic response characteristics at the root of the fan include: blank reflection with low-frequency characteristics; the seismic response characteristics in the middle of the fan include: medium-to-strong amplitude reflection characteristics, medium-to-long continuous phase axis with medium-frequency characteristics; the seismic response characteristics at the tip of the fan include: medium-to-weak amplitude reflection characteristics, medium-to-short continuous phase axis, obvious bifurcation and merging with higher frequencies.

6. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, In step 4), the envelope positions of the fan root, fan middle and fan end of each period are determined on the plane.

7. The method for identifying lithological traps in conglomerate bodies according to claim 1, characterized in that, The sand and conglomerate lithology sensitive parameter mentioned in step 5) is the P-wave impedance, which is obtained by cross-analysis of the natural gamma and P-wave impedance of the wells already drilled in the work area.

8. The method for identifying lithological traps in conglomerate bodies according to claim 7, characterized in that, The longitudinal wave impedance ranges from 11500 to 13500 g / cm. 3 *m / s, porosity range is greater than 6%.

9. The method for identifying lithological traps in conglomerate bodies according to any one of claims 1 to 7, characterized in that, In step 5), the reservoir thickness threshold is set to 10m.

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