A method for predicting thin interbedded type deposition high-quality reservoirs

Abstract

The present application relates to a kind of thin interbed type deposit high-quality reservoir prediction method, comprising: obtaining the geological data, seismic data and well logging data of the region to be analyzed, well seismic combination tracking interpretation oil group top, bottom interface;With the oil group top, bottom interface as constraint, utilize the three-dimensional seismic data acquisition three-dimensional seismic inversion data;With the oil group top, bottom interface as constraint, according to the three-dimensional seismic inversion data and the well logging data are combined, obtain oil group internal relative isochronous sedimentary interface;According to the oil group internal relative isochronous sedimentary interface, based on three-dimensional seismic inversion data, each small layer reservoir plane distribution in oil group is solved;According to the three-dimensional seismic inversion data, based on the information of actual drilling well, sandstone probability body seismic data is solved;Utilize actual drilling well information to construct reservoir classification standard, realize single well reservoir type division;According to the sandstone probability body seismic data, with single well reservoir type as constraint, carry out high-quality reservoir space distribution prediction.

Description

Technical Field

[0001] This invention relates to the field of geological research technology for offshore oilfield development, and in particular to a method for predicting high-quality thin interbedded sedimentary reservoirs under multi-information constraints. Background Technology

[0002] High-quality reservoirs generally refer to relatively good reservoirs within a reservoir with certain development potential. They are an important factor affecting the development of oil and gas fields, directly influencing the deployment of injection and production well networks, the selection of development methods, and the tapping of remaining oil in the later stages of oil and gas field development. However, due to the thin interbedded sedimentary layers, individual reservoir sand bodies are thin, with thin layers of sandstone and mudstone interbedded vertically, and rapid lateral reservoir changes and strong heterogeneity. Especially in the sheet sands and distal bar sand bodies of the delta front, the reservoir spatial distribution is complex due to the frequent changes in delta front channels and the combined effects of waves, making sand body prediction often quite difficult.

[0003] Currently, the prediction of high-quality reservoirs mainly relies on a comprehensive analysis of sand body sedimentary type, development degree and scale, and facies change contact relationships, combined with geological models and injection-production relationships in development wells to determine the spatial distribution of sand bodies. However, these methods primarily target reservoir sand bodies with a certain thickness and scale, with limited predictions for thin interbedded high-quality sedimentary reservoirs where the thickness of a single sand body is far below the seismic resolution. Furthermore, existing technologies are mainly based on dense well network data, and the richness of the basic data also influences the results of high-quality reservoir analysis to some extent. However, under the sparse well network conditions of offshore oil and gas fields (early well spacing is generally greater than 1000m, and locally can reach 200-500m in the middle and later stages), existing high-quality reservoir analysis techniques are insufficient to meet the needs of developing thin interbedded sedimentary reservoirs at sea. Summary of the Invention

[0004] To address the aforementioned issues, the purpose of this application is to provide a method for predicting high-quality thin-interbedded sedimentary reservoirs, which fully utilizes 3D seismic data and drilled well data to conduct qualitative characterization of high-quality thin-interbedded sedimentary reservoirs.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] In a first aspect, this application provides a method for predicting high-quality sedimentary reservoirs with thin interbedded layers, the method comprising:

[0007] Geological data, seismic data, and well logging data of the area to be analyzed are obtained, wherein the seismic data includes three-dimensional seismic data, and the top and bottom interfaces of the oil group are traced and interpreted based on the geological data, seismic data, and well logging data.

[0008] Using the top and bottom interfaces of the oil group as constraints, three-dimensional seismic inversion data are obtained using the three-dimensional seismic data;

[0009] Using the top and bottom interfaces of the oil group as constraints, well-seismic integration is performed based on the three-dimensional seismic inversion data and the well logging data to obtain the relatively isochronous sedimentary interfaces inside the oil group.

[0010] Based on the relatively isochronous sedimentary interfaces within the oil group, the planar distribution of each reservoir layer within the oil group is determined using three-dimensional seismic inversion data.

[0011] Based on the aforementioned three-dimensional seismic inversion data, sandstone probability volume seismic data are obtained based on actual drilling information;

[0012] Reservoir classification standards are constructed using actual drilling information to achieve single-well reservoir type classification;

[0013] Based on the aforementioned sandstone probabilistic seismic data, and constrained by the reservoir type of a single well, the spatial distribution prediction of high-quality reservoirs is carried out.

[0014] In one implementation of the present invention, the step of obtaining a relatively isochronous depositional interface within the oil group by combining well-seismic data with the three-dimensional seismic inversion data and the well logging data, using the top and bottom interfaces of the oil group as constraints, includes:

[0015] Using well logging data and geological data, we conducted high-level sub-cycle analysis of single wells within the oil group and comparative analysis of interconnected wells to identify relatively isochronous sedimentary interfaces within the oil group above ground.

[0016] Using the top and bottom interfaces of the oil group as constraints, scaled stratigraphic slices were created based on 3D seismic inversion data.

[0017] For the aforementioned equal-scale stratigraphic slices, the stratigraphic slices are merged using slice deductive analysis techniques;

[0018] Based on the slice deductive analysis results, the relatively isochronous deposition interface inside the oil group was obtained.

[0019] In one implementation of the present invention, the step of determining the planar distribution of each reservoir layer within the oil group based on three-dimensional seismic inversion data according to the relatively isochronous sedimentary interfaces within the oil group includes:

[0020] Based on the relatively isochronous sedimentary interfaces within the oil group, reservoir-sensitive seismic attributes are extracted using 3D seismic inversion data.

[0021] Based on the relatively isochronous sedimentary interfaces within the oil group and well-seismic interaction, the sand-to-soil ratio of each sub-layer within the actual drilled oil group was statistically analyzed.

[0022] Correlation analysis was performed on the seismically sensitive attributes of the reservoir and the sand-soil ratio of each sublayer to construct a quantitative relationship between seismic attributes and sand-soil ratio;

[0023] Based on the quantitative relationship between seismic attributes and sand-soil ratio conversion, the sand-soil ratio of each sub-layer within the oil group is obtained to characterize the planar distribution of the reservoir.

[0024] In one implementation of the present invention, the step of obtaining sandstone probabilistic volume seismic data based on actual drilling information from the three-dimensional seismic inversion data includes:

[0025] Based on actual drilling information, create a wave impedance-lithology cross-plot;

[0026] Based on the impedance-lithology cross plot, reservoir and non-reservoir impedance thresholds are set, and sandstone probabilistic volume seismic data are obtained based on 3D seismic inversion data.

[0027] In one implementation of the present invention, the step of constructing a reservoir classification standard using actual drilling information to classify single-well reservoir types includes:

[0028] Based on actual drilling information, statistical analysis of target layer attribute information is performed;

[0029] Based on the target layer attribute information, multiple information are combined to construct a reservoir classification and division standard;

[0030] Based on the reservoir classification criteria, obtain the single-well reservoir classification curve.

[0031] In one implementation of the present invention, the step of predicting the spatial distribution of high-quality reservoirs based on the sandstone probability volume seismic data, constrained by the single-well reservoir type, includes:

[0032] Based on the relatively isochronous sedimentary interfaces within the oil group, a structural model is established with the oil group interface and the relatively isochronous sedimentary interfaces within the oil group as constraints.

[0033] Based on the structural model, using the probabilistic seismic data of the sandstone as soft constraints and the single-well reservoir classification curve as hard constraints, numerical simulation is carried out based on the structural model to obtain the predicted data volume of the three-dimensional spatial distribution of the reservoir.

[0034] Based on the reservoir three-dimensional spatial distribution prediction data volume and combined with the reservoir classification criteria, high-quality reservoir three-dimensional spatial distribution data volume is obtained.

[0035] Based on the three-dimensional spatial distribution data of high-quality reservoirs, and constrained by the relatively isochronous sedimentary interfaces within the oil group, the planar distribution of high-quality reservoirs in each sub-layer within the oil group is extracted.

[0036] This invention, by adopting the above technical solutions, has the following advantages: Using the top and bottom interfaces of the oil reservoir as constraints, and based on 3D seismic inversion data, it employs a formation slicing method to obtain relatively isochronous sedimentary interfaces within the oil reservoir through well-seismic interaction, thereby confirming the planar distribution of each sub-layer. Furthermore, combining sandstone probabilistic seismic data and single-well reservoir classification data obtained through inversion, and using geological modeling as a bridge, it obtains the spatial distribution of various reservoirs through model simulation, thereby guiding the deployment of development well networks and providing important technical support for the efficient development and scheme adjustment of underground oil and gas reservoirs. In addition, it also has the following advantages:

[0037] (1) The step-by-step analysis approach for high-quality reservoirs in thin interbedded sedimentary formations is adopted. First, based on seismic inversion and constrained by the relative isochronous sedimentary interface, the planar distribution of each small layer of reservoirs at the seismic scale of the first level of thin interbedded sedimentary formations is determined. Then, combined with sandstone probabilistic volume seismic data and single-well reservoir classification information, the high-quality reservoirs of the second level of thin interbedded sedimentary formations are characterized by numerical simulation, thereby improving the accuracy of qualitative characterization of high-quality reservoirs.

[0038] (2) The well-seismic multi-information analysis method is adopted. The rich three-dimensional seismic information is used as a soft constraint and the actual drilling information is used as a hard constraint. The multi-information fusion finally realizes the prediction of thin interbedded sedimentary high-quality reservoirs, thereby making up for the shortcomings of the method of conducting analysis of thin interbedded sedimentary high-quality reservoirs based on well information under the condition of sparse well network at sea, and effectively reducing the uncertainty of high-quality reservoir prediction. Attached Figure Description

[0039] Figure 1 A flowchart of a method for predicting high-quality thin interbedded sedimentary reservoirs provided in an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram of the top and bottom interfaces of an oil column based on three-dimensional seismic data tracking and interpretation, provided in an embodiment of the present invention.

[0041] Figure 3 This is a schematic diagram of the longitudinal relative isochronous deposition interface inside the oil group obtained by well-seismic interaction according to an embodiment of the present invention;

[0042] Figure 4 This is a schematic diagram of the planar distribution of small reservoir layers within an oil group obtained based on three-dimensional seismic inversion data, provided in an embodiment of the present invention.

[0043] Figure 5 This is a seismic profile of sandstone probability volume obtained from three-dimensional seismic inversion data, provided in an embodiment of the present invention.

[0044] Figure 6 This invention provides an example diagram of a reservoir classification standard that combines real drilling information and multiple information sources, as well as a single-well reservoir type classification standard.

[0045] Figure 7 A schematic diagram of high-quality reservoir spatial distribution prediction provided in this embodiment of the invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0047] This addresses the issue that existing high-quality reservoir analysis techniques are insufficient to meet the needs of developing thin interbedded sedimentary reservoirs at sea. This invention provides a method for predicting high-quality thin-interbedded sedimentary reservoirs, comprising: acquiring geological data, seismic data, and well logging data of the area to be analyzed, wherein the seismic data includes 3D seismic data, and performing well-seismic integration to trace and interpret the top and bottom interfaces of the oil group based on the geological data, seismic data, and well logging data; using the top and bottom interfaces of the oil group as constraints, obtaining 3D seismic inversion data using the 3D seismic data; using the top and bottom interfaces of the oil group as constraints, performing well-seismic integration based on the 3D seismic inversion data and the well logging data to obtain the relatively isochronous sedimentary interfaces within the oil group; determining the planar distribution of each small layer of reservoir within the oil group based on the relatively isochronous sedimentary interfaces within the oil group and the 3D seismic inversion data; obtaining sandstone probabilistic volume seismic data based on actual drilling information based on the 3D seismic inversion data; constructing a reservoir classification standard using the actual drilling information to achieve single-well reservoir type classification; and predicting the spatial distribution of high-quality reservoirs based on the sandstone probabilistic volume seismic data and constrained by the single-well reservoir type. Make full use of 3D seismic data and drilled well data to conduct qualitative characterization of thin interbedded high-quality sedimentary reservoirs.

[0048] The above methods and processes are described below in more detail in some embodiments, with reference to more accompanying drawings of the present invention.

[0049] Example 1 provides a qualitative characterization method for the connectivity of channel sand bodies with relative isochronous interface constraints, such as... Figure 1 As shown, it includes the following steps:

[0050] Step A: Using 3D seismic data, combining well and seismic data, we can perform profile and interactive tracking to interpret the top and bottom interfaces of the oil group;

[0051] Depend on Figure 2 It can be seen that, based on three-dimensional seismic data, the top and bottom interfaces of the target sedimentary I oil group and II oil group can be traced and interpreted.

[0052] Step B: Based on the 3D seismic data, and using the top and bottom interfaces of the oil group as constraints, obtain 3D seismic inversion data;

[0053] Step C involves using 3D seismic inversion data, with the top and bottom interfaces of the oil group as constraints, and combining well and seismic data to obtain the relatively isochronous sedimentary interfaces within the oil group. The specific steps are as follows:

[0054] Step C1: Select a typical well, perform wavelet transform on the GR curve, and perform single-well and series-well sequence analysis based on the curve characteristics to obtain the initial relative isochronous sedimentary interface above the well.

[0055] Step C2: Using the top and bottom interfaces of the II oil group as constraints, create stratigraphic slices at a proportional scale based on the 3D seismic inversion data;

[0056] Step C3: Combining the initial relative isochronous sedimentary interfaces from the well, and based on the sedimentary geological characteristics, the stratigraphic slices are merged at the same scale using slice deduction to obtain the initial relative isochronous sedimentary interfaces;

[0057] Step C4: Using the initial relative isochronous sedimentary interface as a constraint, the relative isochronous sedimentary interface is optimized based on the three-dimensional seismic inversion data through "well-seismic interaction" to obtain the final relative isochronous sedimentary interface inside Group II.

[0058] Depend on Figure 3 It can be seen that the relative isochronous deposition interface divides the interior of the target II oil group into four sub-layers, SQ1 to SQ4.

[0059] Step D involves determining the planar distribution of each reservoir layer within the oil group based on three-dimensional seismic inversion data, constrained by the relatively isochronous sedimentary interfaces within the oil group. The specific steps are as follows:

[0060] Step D1: Using the relative isochronous sedimentary interface as a constraint, select appropriate time windows above and below, and extract seismic attributes characterizing the reservoir based on the three-dimensional seismic inversion data;

[0061] Step D2: Using the top and bottom interfaces of the oil group and the relatively isochronous sedimentary interfaces within it as constraints, calculate the sand-soil ratio of the actual drilled well reservoir.

[0062] Step D3: Perform correlation analysis on the seismic attributes and reservoir sand-soil ratio extracted from the SQ3 sub-layer within the II oil group, select the reservoir sensitive seismic attributes, and calibrate the attributes in conjunction with the actual drilled reservoir sand-soil ratio;

[0063] Depend on Figure 4 It can be seen that the SQ3 layer within the II oil group exhibited characteristics of dual source supply during its deposition period. The sedimentary bodies were distributed in a northwest-southeast direction, with the northern sedimentary bodies being larger in scale and having more developed reservoirs than the southern sedimentary bodies.

[0064] Step E involves using 3D seismic inversion data to obtain sandstone probabilistic volume seismic data based on actual well information. The specific steps are as follows:

[0065] Step E1: Using the well logging stratification of the top interface of the oil group as the time window, create a wave impedance-lithology cross plot;

[0066] Step E2: Based on the cross-intersection analysis results, set the impedance threshold values ​​for reservoir and non-reservoir areas, and then obtain sandstone probabilistic volume seismic data based on the 3D seismic inversion data.

[0067] Figure 5 In the seismic profile of sandstone probability bodies, the probability range of sandstone is 0 to 1, and the redder the color, the greater the probability of sandstone development.

[0068] Step F involves using actual drilling information and combining multiple pieces of information to construct a reservoir classification standard, thereby classifying the reservoir type of a single well. The specific steps are as follows:

[0069] Step F1: Based on actual drilling information, statistically analyze the porosity, permeability, grain size, lithology, and other information of the target layer, using the top and bottom layers of the oil group as constraints;

[0070] Step F2: Based on the statistical results, set threshold values ​​for different types of reservoir parameters, and combine multiple information to construct a reservoir classification standard;

[0071] Step F3: Based on the reservoir classification criteria, obtain the single-well reservoir category classification curve.

[0072] Depend on Figure 6 It can be seen that, based on reservoir parameters such as porosity and permeability, reservoirs are divided into four categories. Among them, reservoirs I and II have better physical properties and can be considered high-quality reservoirs, while reservoirs III and IV have poorer physical properties and are considered secondary reservoirs. Taking Well-1 as an example...

[0073] For example, the SQ1 and SQ3 layers of this well are mainly composed of reservoirs I and II; the SQ2 layer is mainly composed of reservoirs I and IV.

[0074] Step G involves using the single-well reservoir type classification as a constraint to predict the spatial distribution of high-quality reservoirs. The specific steps are as follows:

[0075] Step G1: Establish a structural model with constraints on the oil group interface and the relatively isochronous deposition interface within the oil group;

[0076] Step G2: Based on the structural model, using sandstone probability volume seismic data as soft constraints and single-well reservoir classification curves as hard constraints, numerical simulation is carried out to obtain the three-dimensional spatial distribution prediction data volume of reservoir types.

[0077] Step G3: Based on the three-dimensional spatial distribution prediction data volume of reservoir type, and combined with the reservoir classification criteria, set the codes for various types of reservoirs, and then obtain the three-dimensional spatial distribution data volume of various types of reservoirs;

[0078] Step G4: Based on the three-dimensional spatial distribution data of various reservoirs, and using the relatively isochronous sedimentary interface within the oil group as the time window, extract the planar distribution of high-quality reservoirs in each sub-layer within the oil group.

[0079] Depend on Figure 7 It can be seen that the SQ3 sublayer Well-1 and Well-12 well areas within the II oil group mainly develop Class I and II reservoirs, with some Class III reservoirs; the Well-3 and Well-14 well areas mainly develop Class III reservoirs, with fewer Class I and II reservoirs.

[0080] In the several embodiments provided by this invention, it should be understood that the disclosed methods can be implemented in other ways. For example, the embodiments described above are merely illustrative.

[0081] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting high-quality sedimentary reservoirs with thin interbedded layers, characterized in that, The method includes: Geological data, seismic data, and well logging data of the area to be analyzed are obtained, wherein the seismic data includes three-dimensional seismic data, and the top and bottom interfaces of the oil group are traced and interpreted based on the geological data, seismic data, and well logging data. Using the top and bottom interfaces of the oil group as constraints, three-dimensional seismic inversion data are obtained using the three-dimensional seismic data; Using the top and bottom interfaces of the oil group as constraints, well-seismic integration is performed based on the three-dimensional seismic inversion data and the well logging data to obtain the relatively isochronous sedimentary interfaces inside the oil group. Based on the relatively isochronous sedimentary interfaces within the oil group, the planar distribution of each reservoir layer within the oil group is determined using three-dimensional seismic inversion data. Based on the aforementioned three-dimensional seismic inversion data, sandstone probability volume seismic data are obtained based on actual drilling information; Reservoir classification standards are constructed using actual drilling information to achieve single-well reservoir type classification; Based on the aforementioned sandstone probabilistic seismic data, and constrained by the reservoir type of a single well, the spatial distribution prediction of high-quality reservoirs is carried out.

2. The method for predicting high-quality sedimentary reservoirs of thin interbedded layers according to claim 1, characterized in that, The process involves using the top and bottom interfaces of the oil group as constraints, and combining well-seismic data with the three-dimensional seismic inversion data to obtain relatively isochronous sedimentary interfaces within the oil group, including: Using well logging data and geological data, we conducted high-level sub-cycle analysis of single wells within the oil group and comparative analysis of interconnected wells to identify relatively isochronous sedimentary interfaces within the oil group above ground. Using the top and bottom interfaces of the oil group as constraints, scaled stratigraphic slices were created based on 3D seismic inversion data. For the aforementioned equal-scale stratigraphic slices, the stratigraphic slices are merged using slice deductive analysis techniques; Based on the slice deductive analysis results, the relatively isochronous deposition interface inside the oil group was obtained.

3. The method for predicting high-quality sedimentary reservoirs of thin interbedded layers according to claim 2, characterized in that, The step of determining the planar distribution of each reservoir layer within the oil group based on the relatively isochronous sedimentary interfaces within the oil group and using three-dimensional seismic inversion data includes: Based on the relatively isochronous sedimentary interfaces within the oil group, reservoir-sensitive seismic attributes are extracted using 3D seismic inversion data. Based on the relatively isochronous sedimentary interfaces within the oil group and well-seismic interaction, the sand-to-soil ratio of each sub-layer within the actual drilled oil group was statistically analyzed. Correlation analysis was performed on the seismically sensitive attributes of the reservoir and the sand-soil ratio of each sublayer to construct a quantitative relationship between seismic attributes and sand-soil ratio; Based on the quantitative relationship between seismic attributes and sand-soil ratio conversion, the sand-soil ratio of each sub-layer within the oil group is obtained to characterize the planar distribution of the reservoir.

4. The method for predicting high-quality sedimentary reservoirs of thin interbedded layers according to claim 3, characterized in that, The step of obtaining sandstone probabilistic volume seismic data based on the three-dimensional seismic inversion data and actual drilling information includes: Based on actual drilling information, create a wave impedance-lithology cross-plot; Based on the impedance-lithology cross plot, reservoir and non-reservoir impedance thresholds are set, and sandstone probabilistic volume seismic data are obtained based on 3D seismic inversion data.

5. The method for predicting high-quality sedimentary reservoirs of thin interbedded layers according to claim 4, characterized in that, The method of constructing reservoir classification standards using actual drilling information to classify reservoir types in single wells includes: Based on actual drilling information, statistical analysis of target layer attribute information is performed; Based on the target layer attribute information, multiple information are combined to construct a reservoir classification and division standard; Based on the reservoir classification criteria, obtain the single-well reservoir classification curve.

6. The method for predicting high-quality sedimentary reservoirs of thin interbedded layers according to claim 5, characterized in that, The prediction of the spatial distribution of high-quality reservoirs based on the sandstone probability volume seismic data, constrained by the single-well reservoir type, includes: Based on the relatively isochronous sedimentary interfaces within the oil group, a structural model is established with the oil group interface and the relatively isochronous sedimentary interfaces within the oil group as constraints. Based on the structural model, using sandstone probability volume seismic data as soft constraints and single-well reservoir classification curves as hard constraints, numerical simulations are conducted to obtain reservoir three-dimensional spatial distribution prediction data volumes. Based on the reservoir three-dimensional spatial distribution prediction data volume and combined with the reservoir classification criteria, high-quality reservoir three-dimensional spatial distribution data volume is obtained. Based on the three-dimensional spatial distribution data of high-quality reservoirs, and constrained by the relatively isochronous sedimentary interfaces within the oil group, the planar distribution of high-quality reservoirs in each sub-layer within the oil group is extracted.

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