CN117849874A - Prediction method of dolomite vuggy thin reservoir based on reservoir genetic geological model - Google Patents

Abstract

The invention provides a dolomite pore type thin reservoir prediction method based on a reservoir cause geological model, which comprises the following steps: acquiring and analyzing field section, core, logging and seismic data; dividing stratum sequence and analyzing the filling rule of stratum sequence stratum; establishing a reservoir formation mechanism and a predictive geological model of a target interval hole type dolomite reservoir of a research area; performing paleomorphology restoration in a deposition period on the stratum on the basis of fine interpretation of the three-dimensional earthquake; analyzing the seismic response characteristics of the reservoir by combining forward modeling; according to the paleo-landform restoration result, the sensitive seismic attribute is optimized, and the favorable phase zone is determined; under the constraint of plane spread of paleo-topography in a deposition period, carrying out phase control high-resolution waveform indication inversion; and determining a thin reservoir spreading rule of the research area according to the inversion result, and quantitatively predicting the dolomite pore type thin reservoir of the research area. The invention can accurately score favorable reservoir zone distribution and provide new ideas and directions for reservoir prediction with similar characteristics.

Description

Prediction method of dolomite vuggy thin reservoir based on reservoir genetic geological model

Technical Field

The invention belongs to the technical field of petroleum exploration and development, and in particular is a method for predicting dolomite hole-type thin reservoirs based on a reservoir genetic geological model.

Background technique

More and more drilling and research have shown that the development of deep-to-ultra-deep carbonate-scale phase-controlled reservoirs is closely related to sea level rise and fall, and has the characteristics of thin single layer thickness, multiple layers stacked vertically, and strong lateral heterogeneity. The scale of this type of reservoir is often smaller than the seismic resolution and difficult to accurately predict. Regarding the prediction of this type of carbonate phase-controlled thin reservoir, previous studies have shown that sedimentary micro-topography restoration is an effective method for predicting phase-controlled thin reservoirs, and its accuracy far exceeds that of geophysical prediction. For sparse well network areas in the exploration and evaluation stage, how to combine well-seismic reconstruction of sedimentary micro-topography, and combine it with the predictive geological model formed by the early exposure karst time driven by multi-level sea level rise and fall, to accurately predict the porous thin reservoirs formed by medium- and long-term exposure, is still a major problem.

Summary of the invention

The present invention proposes a prediction method for dolomite vug-type thin reservoirs based on reservoir genetic geological model, making full use of abundant coring, macro-micro and 3D seismic data, analyzing the sequence position and stratigraphic thickness significance of the Mao Er Xia sub-section, reconstructing the sedimentary paleo-geomorphology of the Mao Er Xia sub-section in the late high position, and predicting the distribution of favorable reservoir zones on the basis of clarifying the genesis and geological model of the vug-type thin reservoirs of the Mao Er Xia sub-section, forming a comprehensive geological-geophysical prediction method for deep and ultra-deep vug-type thin reservoirs, which can provide new ideas for the prediction of similar characteristic reservoirs. .

In order to achieve the above object, the technical solution of the present invention is as follows:

The method for predicting dolomite vug-type thin reservoir based on reservoir genetic geological model includes the following steps:

Step 1: Collect and organize field profiles, cores, well logging and seismic data of the target layer in the study area;

Step 2: Use the field profiles, core and logging data in step 1 to divide the single well sequence, establish a stratigraphic framework for connected wells, determine the stratigraphic filling rules of the target layer, and clarify the geological significance of the stratigraphic thickness.

Step 3: According to the sequence stratigraphic division scheme in step 2, analyze the characteristics of dolomite vuggy reservoirs, clarify the reservoir formation mechanism of dolomite vuggy reservoirs within the sequence framework, and determine the corresponding reservoir prediction geological model;

Step 4: Based on the sequence division scheme in step 2 and the 3D seismic fine interpretation, carry out paleo-geomorphological restoration of the target layer section in the study area during the sedimentary period to determine its paleo-geomorphological characteristics during the sedimentary period;

Step 5: Based on the collected drilling data and seismic data, conduct seismic forward simulation to determine the seismic response characteristics of the reservoir in the target layer of the study area;

Step 6: Based on the reservoir seismic response characteristics in step 5, select sensitive seismic attributes and determine the distribution of favorable phase belts in the study area;

Step 7: Under the constraints of the paleo-geomorphic features in step 4 and the distribution law of the favorable phase belt in step 6, high-resolution waveform indication inversion is carried out;

Step 8: Based on the high-resolution waveform indication inversion results in step 7, determine the vertical and horizontal distribution patterns of the dolomite porous thin reservoirs in the entire area, and make quantitative predictions on the dolomite porous thin reservoirs in the study area.

further:

The data described in step 1 include field dolomite prototype profiles, coring data, core thin section data, drilling and logging data, conventional logging curves, layered data, single well test production capacity data, and three-dimensional seismic data.

The specific steps of determining the stratigraphic filling law of the target layer section in step 2 are as follows: taking sedimentary cycles as units, identifying the characteristics of the sequence interfaces through lithology, conventional logging, and imaging logging, and dividing the single well sequences; establishing a stratigraphic framework for connected well sequences in the study area; and determining the stratigraphic filling law of the target layer section in combination with the sedimentary background of the study area, and clarifying the geological significance of the stratigraphic thickness.

In step three, the prediction geological model of dolomite vug-type reservoirs is determined as follows: based on the petrological and geochemical characteristics of dolomite reservoirs, the relationship between lithology and lithofacies and reservoir development is analyzed, the relationship between karst and reservoir development is analyzed, the dolomitization pattern is confirmed, the reservoir formation mechanism of dolomite vug-type reservoirs within the stratigraphic framework is clarified, and the corresponding reservoir prediction geological model is determined.

The specific steps for determining the paleogeomorphic features of the sedimentary period in step 4 are as follows: based on the 3D seismic data volume, single-well synthetic records are produced using acoustic waves and density logging curves, the top and bottom interfaces of the target layer and the interfaces of the upper and lower strata of the target layer are calibrated, a regional framework profile is established, and a detailed 3D seismic interpretation is performed for the entire area to clarify the distribution characteristics of the stratigraphic thickness of the target layer in the study area; on the basis of clarifying the geological significance of the stratigraphic thickness, a reasonable paleogeomorphic restoration method for the sedimentary period is selected to determine the paleogeomorphic features of the sedimentary period.

The specific steps of determining reservoir seismic response characteristics in step five are as follows: analyzing the seismic response characteristics of single-well reservoirs; statistically analyzing the physical characteristics of the formations and reservoir rocks of the target layer, determining the rock physical parameters, and conducting seismic forward modeling; and comprehensively analyzing the seismic response characteristics of single-well reservoirs and seismic forward modeling results to determine the seismic response characteristics of the reservoirs of the target layer in the study area.

The high-resolution waveform indication inversion in step seven is specifically as follows: data preprocessing, including removing outliers from logging curves, curve standardization, reservoir sensitivity curve analysis, curve reconstruction, and making synthetic records; then setting the stratigraphic contact relationship based on seismic reflection characteristics and sedimentary laws, and calculating the initial low-frequency framework model; determining the lateral variogram based on the planar distribution law of the favorable phase belt, and determining the vertical variogram based on the logging information.

The specific vertical and horizontal distribution patterns of the thin dolomite vug-type reservoirs in the study area determined in step eight are as follows: based on the waveform indication inversion results, the reservoir time thickness of the target layer is extracted as a reservoir time thickness map; based on the logging and seismic data, the average layer velocity of the target layer reservoir is statistically analyzed, and the time-depth conversion is performed in combination with the reservoir time thickness to obtain a reservoir thickness map; combined with the favorable phase belt distribution map and the sedimentary period paleo-geomorphology map for comprehensive analysis, the dolomite vug-type thin reservoirs in the study area are quantitatively predicted.

The following beneficial effects will be achieved by adopting the above scheme:

(1) Analysis of petrological and geochemical characteristics of dolomite reservoirs The essential genesis of dolomite reservoirs is analyzed. The development of dolomite vug reservoirs is closely related to the shallowing sequence. The karstification has typical early diagenetic karst characteristics such as internal exposure surface, karst spots, semi-dissociation zones and brecciation. In addition, the dolomite at the edge of the karst system and the dolomite powder in the filling have dissolution edges and dolomite micrite. This indicates that dolomitization and karstification are both developed in the early diagenetic period controlled by the sequence interface. The development of this type of early diagenetic phase-controlled karst reservoir is controlled by the paleo-geomorphology and grain beach during the sedimentary period. The reservoir prediction geological model established on this basis has macroscopic geological significance and can better understand the environment and history of dolomite formation.

(2) Paleogeomorphological restoration of the target layer during the sedimentary period based on the reservoir genetic geological model can better assist the prediction of favorable phase belts. The prediction of favorable phase belts is often a complex issue that requires comprehensive research from multiple aspects. Paleogeomorphological analysis can provide important references for the prediction of favorable phase belts, reservoir inversion and other studies, thereby more accurately predicting dolomite reservoirs.

(3) It can make good use of the mapping relationship between the paleo-geomorphology during the sedimentary period and the favorable phase belt to constrain the interpolation range of the model during the inversion process. The inversion results have obvious phase-controlled characteristics and can effectively improve the accuracy of the comprehensive geological-geophysical prediction of deep and ultra-deep porous thin reservoirs.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a flow chart of the method of the present invention;

FIG2 is a lateral comparison diagram of sequence stratigraphy in the embodiment;

FIG3 is a diagram of a reservoir prediction geological model in an embodiment;

Fig. 4 is a sedimentary paleo-geomorphology diagram in the embodiment;

FIG5 is a diagram of a seismic forward modeling of reservoir development and its results in an embodiment;

FIG6 is a plan view of the favorable phase belt in the embodiment;

FIG7 is a cross section of an over-realized drilling waveform indication inversion result in an embodiment;

FIG8 is a thickness distribution diagram of the target layer dolomite vuggy reservoir in the embodiment.

Detailed ways

The specific technical solution of the present invention is explained in conjunction with embodiments.

This embodiment conducts a comprehensive study on the dolomite vug-type thin reservoir in the lower sub-member of the second member of the Maokou Formation in the Hechuan-Wusheng area in the central Sichuan Basin, as shown in the process of FIG1 :

Step 1: Collect and organize the field profiles, core, logging and seismic data of the lower sub-member of Mao Er in the study area; specifically including field dolomite prototype profiles, coring data, core thin section data, drilling and logging data, conventional logging curves, stratification data, single well test production capacity data, and three-dimensional seismic data.

Step 2: Use the field profiles, core and logging data in step 1 to divide the single well sequence, establish a stratigraphic framework of connected well sequences, and determine the stratigraphic filling law of the target layer segment, as shown in Figure 2; specifically: take sedimentary cycles as units, identify the characteristics of sequence interfaces through lithology, conventional logging and imaging logging, and divide the single well sequence; establish a stratigraphic framework of connected well sequences in the study area; combine the sedimentary background of the study area to determine the stratigraphic filling law of the target layer segment and clarify the geological significance of the stratigraphic thickness.

Step 3: According to the sequence stratigraphic division scheme in step 2, the characteristics of dolomite vug reservoirs are analyzed, the reservoir formation mechanism of dolomite vug reservoirs within the sequence framework is clarified, and the corresponding reservoir prediction geological model is determined, as shown in Figure 3. The specific method is: based on the petrological and geochemical characteristics of the dolomite reservoir, the relationship between lithology and lithofacies and reservoir development is analyzed, the relationship between karst and reservoir development is analyzed, the dolomitization pattern is confirmed, the reservoir formation mechanism of dolomite vug reservoirs within the sequence framework is clarified, and the corresponding reservoir prediction geological model is determined.

Step 4: According to the stratigraphic division scheme in step 2 and the 3D seismic interpretation, the paleogeomorphology restoration of the target layer in the study area during the sedimentary period is carried out to determine its paleogeomorphological characteristics during the sedimentary period, as shown in Figure 4; specifically: based on the 3D seismic data body, the single-well synthetic record is produced using the acoustic wave and density logging curves, the top and bottom interfaces of the target layer and the upper and lower stratigraphic interfaces of the target layer are calibrated, a regional framework profile is established, and a 3D seismic interpretation is carried out for the entire area to clarify the stratigraphic thickness distribution characteristics of the target layer in the study area; on the basis of clarifying the geological significance of the stratigraphic thickness, a reasonable method for paleogeomorphological restoration during the sedimentary period is selected to determine the paleogeomorphological characteristics of the sedimentary period.

Step 5: Based on the collected drilling data and seismic data, conduct seismic forward modeling to determine the seismic response characteristics of the target layer reservoir in the study area, as shown in Figure 5; specifically: analyze the seismic response characteristics of the single well reservoir; statistically analyze the rock physical characteristics of the target layer and reservoir, determine the rock physical parameters, and conduct seismic forward modeling; comprehensively analyze the seismic response characteristics of the single well reservoir and the seismic forward modeling results to determine the seismic response characteristics of the target layer reservoir in the study area.

Step 6: According to the reservoir seismic response characteristics in step 5, select sensitive seismic attributes and determine the distribution of favorable phase belts in the study area, as shown in Figure 6;

Step 7: Under the constraints of the paleomorphic features in step 4 and the distribution law of the favorable phase belt in step 6, high-resolution waveform indication inversion is carried out, as shown in Figure 7; specifically: data preprocessing, including removing outliers from logging curves, curve standardization, reservoir sensitivity curve analysis, curve reconstruction, and making synthetic records; then setting the stratigraphic contact relationship based on seismic reflection characteristics and sedimentary laws, and calculating the initial low-frequency frame model; determining the lateral variogram based on the planar distribution law of the favorable phase belt, and determining the vertical variogram based on the logging information.

Step 8: According to the high-resolution waveform indication inversion results in step 7, the vertical and horizontal distribution rules of the dolomite vug-type thin reservoir in the whole area are determined, and the dolomite vug-type thin reservoir in the study area is quantitatively predicted, as shown in Figure 8. Specifically: according to the waveform indication inversion results, the reservoir time thickness of the target layer is extracted as the reservoir time thickness map; according to the logging and seismic data, the average layer velocity of the target layer reservoir is statistically analyzed, and the time-depth conversion is performed in combination with the reservoir time thickness to obtain the reservoir thickness map; combined with the favorable phase belt distribution map and the sedimentary period paleo-geomorphology map for comprehensive analysis, the dolomite vug-type thin reservoir in the study area is quantitatively predicted.

Claims (8)

1. A method for predicting dolomite vug-type thin reservoirs based on a reservoir genetic geological model, characterized in that it comprises the following steps: Step 1: Collect and organize the target layer data in the study area; Step 2: Divide the data in step 1 into single well sequences, establish a stratigraphic framework for connected well sequences, determine the filling rules of the target layer, and clarify the geological significance of the stratigraphic thickness; Step 3: According to the sequence stratigraphic division scheme in step 2, analyze the characteristics of dolomite vuggy reservoirs, clarify the reservoir formation mechanism of dolomite vuggy reservoirs within the sequence framework, and determine the corresponding reservoir prediction geological model; Step 4: Based on the sequence division scheme in step 2 and the 3D seismic fine interpretation, carry out paleo-geomorphological restoration of the target layer section in the study area during the sedimentary period to determine its paleo-geomorphological characteristics during the sedimentary period; Step 5: Based on the collected drilling data and seismic data, conduct seismic forward simulation to determine the seismic response characteristics of the reservoir in the target layer of the study area; Step 6: Based on the reservoir seismic response characteristics in step 5, select sensitive seismic attributes and determine the distribution of favorable phase belts in the study area; Step 7: Under the constraints of the paleo-geomorphic features in step 4 and the distribution law of the favorable phase belt in step 6, high-resolution waveform indication inversion is carried out; Step 8: Based on the high-resolution waveform indication inversion results in step 7, determine the vertical and horizontal distribution patterns of the dolomite porous thin reservoirs in the entire area, and make quantitative predictions on the dolomite porous thin reservoirs in the study area. 2. The method for predicting dolomite vug-type thin reservoirs based on a reservoir genetic geological model according to claim 1 is characterized in that the data in step one include field dolomite prototype profiles, coring data, core thin section data, drilling and logging data, conventional logging curves, stratification data, single well test production capacity data, and three-dimensional seismic data. 3. According to the method for predicting dolomite vug-type thin reservoirs based on the reservoir genetic geological model described in claim 1, it is characterized in that the determination of the stratigraphic filling law of the target layer segment in step 2 is specifically as follows: taking sedimentary cycles as units, identifying the characteristics of the stratigraphic interface through lithology, conventional logging, and imaging logging, and dividing the single well sequence; establishing a stratigraphic framework for connected well sequences in the study area; combining the sedimentary background of the study area, determining the stratigraphic filling law of the target layer segment, and clarifying the geological significance of the stratigraphic thickness. 4. The method for predicting dolomite porous thin reservoirs based on the reservoir genetic geological model according to claim 1 is characterized in that the reservoir prediction geological model is determined in step three as follows: based on the petrological and geochemical characteristics of the dolomite reservoir, the relationship between lithology and lithofacies and reservoir development is analyzed, the relationship between karst and reservoir development is analyzed, the dolomitization pattern is confirmed, the reservoir formation mechanism of the dolomite porous reservoir within the stratigraphic framework is clarified, and the corresponding reservoir prediction geological model is determined. 5. The method for predicting dolomite vug-type thin reservoirs based on a reservoir genetic geological model according to claim 1 is characterized in that the determination of the paleogeomorphic features of the sedimentary period in step 4 is specifically as follows: based on the three-dimensional seismic data body, single-well synthetic records are made using acoustic waves and density logging curves, the top and bottom interfaces of the target layer and the upper and lower stratum interfaces of the target layer are calibrated, a regional framework profile is established, and a detailed three-dimensional seismic interpretation is performed in the entire area to clarify the distribution characteristics of the stratum thickness of the target layer section in the study area; on the basis of clarifying the geological significance of the stratum thickness, a reasonable paleogeomorphic restoration method of the sedimentary period is selected to determine the paleogeomorphic features of the sedimentary period. 6. According to the method for predicting dolomite vug-type thin reservoirs based on the reservoir genetic geological model described in claim 1, it is characterized in that determining the reservoir seismic response characteristics in step five is specifically: analyzing the seismic response characteristics of the reservoir in a single well; statistically analyzing the rock physical characteristics of the target layer and reservoir, determining the rock physical parameters, and conducting seismic forward modeling; comprehensively analyzing the seismic response characteristics of the reservoir in a single well and the seismic forward modeling results, and determining the seismic response characteristics of the reservoir in the target layer of the study area. 7. According to the method for predicting dolomite vug-type thin reservoirs based on the reservoir genetic geological model described in claim 1, it is characterized in that the high-resolution waveform indication inversion in step seven specifically includes: data preprocessing, including removing outliers from logging curves, curve standardization, reservoir sensitivity curve analysis, curve reconstruction, and making synthetic records; then setting the stratigraphic contact relationship based on seismic reflection characteristics and sedimentary laws, and calculating the initial low-frequency framework model; determining the lateral variation function based on the planar distribution law of the favorable phase belt, and determining the vertical variation function based on the logging information. 8. The method for predicting dolomite vug-type thin reservoirs based on a reservoir genetic geological model according to claim 1 is characterized in that the vertical and horizontal distribution patterns of the dolomite vug-type thin reservoirs in the study area are determined in step eight as follows: according to the waveform indication inversion results, the reservoir time thickness of the target layer is extracted as a reservoir time thickness map; according to logging and seismic data, the average layer velocity of the target layer reservoir is statistically analyzed, and time-to-depth conversion is performed in combination with the reservoir time thickness to obtain a reservoir thickness map; combined with a comprehensive analysis of the favorable phase belt distribution map and the paleo-geomorphological map of the sedimentary period, a quantitative prediction of the dolomite vug-type thin reservoirs in the study area is performed.