A forward sand content prediction method based on deposition cycle constraint

Abstract

The application discloses a kind of based on sedimentary cycle constraint under forward sandstone content prediction method, the prediction method includes: step S1: collection target area three-dimensional poststack and prestack data;Step S2: according to the three-dimensional poststack and prestack data value obtains multi-well geologic model;Step S3: according to the multi-well geologic model forms forward model;Step S4: using the forward model obtains sandstone percentage content plan;Step S5: contrast verification obtains zone sandstone percentage content. Both continuous sampling seismic information is used, well data is also considered, and is consistent with geological understanding, improve prediction accuracy.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration, and in particular to a forward modeling method for predicting sandstone content based on sedimentary cycle constraints. Background Technology

[0002] The Jiyang Depression uplift area is a favorable location for discovering large and medium-sized oil and gas reservoirs. Large and medium-sized oil and gas fields have already been discovered in the Chengdong, Gudao, Gudong, Kendong, and Chengbei uplift areas of the Jiyang Depression. The main reservoir types are structural, lithological, stratigraphic, and complex reservoirs. With the increasing level of oil and gas exploration, the difficulty of exploration is also increasing, requiring increasingly precise exploration work. The presence of reservoirs and reservoir boundaries are key challenges in exploration. Therefore, accurately characterizing the percentage content of sandstone is the most fundamental and important task in oil and gas exploration.

[0003] Lithology is a crucial factor influencing seismic wave propagation velocity; therefore, the planar distribution pattern of sandstone percentage content is based on seismic wave propagation velocity. Currently, there are two main methods for studying sandstone percentage content using seismic wave velocity data: the plate method and the seismic attribute method. Because the lithology of shallow strata in the Shengli exploration area varies rapidly both laterally and vertically, exhibiting poor continuity, using only well data and sand / mudstone velocity plates to study sandstone distribution in this area is not only difficult but also lacks accuracy. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a forward modeling method for predicting sandstone content based on sedimentary cycle constraints, which overcomes or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a forward modeling method for predicting sandstone content based on sedimentary cycle constraints is provided, the prediction method comprising:

[0006] Step S1: Collect 3D post-stack and pre-stack data of the target region;

[0007] Step S2: Obtain a multi-well geological model based on the three-dimensional post-stack and pre-stack data;

[0008] Step S3: Generate a forward model based on the multi-well geological model;

[0009] Step S4: Obtain a planar map of sandstone percentage content using the forward model;

[0010] Step S5: Compare and verify to obtain the percentage content of sandstone in the zone.

[0011] Optionally, step S2: obtaining a multi-well geological model based on the three-dimensional post-stack and pre-stack data specifically includes:

[0012] A single-well geological model is established based on the three-dimensional post-stack and pre-stack data, and a multi-well geological model is obtained by lithological interpolation based on sedimentary facies analysis.

[0013] Optionally, step S3: forming a forward model based on the multi-well geological model specifically includes:

[0014] Based on the multiple sandstone percentage reservoirs in the multi-well geological model, corresponding acoustic and density values ​​are assigned to form a forward model.

[0015] Optionally, step S4: obtaining a sandstone percentage content planar map using the forward model specifically includes: using the forward model to simulate earthquake data to predict the distribution range of different seismic facies, and then combining the relationship established between the seismic facies and the sandstone percentage content to obtain a sandstone percentage content planar map.

[0016] Optionally, step S5: comparing and verifying the percentage content of sandstone in the zone specifically includes:

[0017] The actual sandstone thickness of wells involved in the prediction and those not involved in the prediction were compared with the prediction results to verify the percentage content of sandstone in the zone.

[0018] Optionally, the collection of three-dimensional post-stack and pre-stack data of the target region specifically includes:

[0019] Collect three-dimensional post-stack and pre-stack seismic data, well logging data, well logging data, and lithological data of the target area to prepare the data;

[0020] The pre-stack gathering data of the work area were processed by overlaying at an angle of 3-13° and then finely synthesized and calibrated.

[0021] Optionally, the step of establishing a single-well geological model based on the three-dimensional post-stack and pre-stack data, and obtaining a multi-well geological model by lithological interpolation based on sedimentary facies analysis, specifically includes:

[0022] Based on the lithological and electrical characteristics, the sedimentary cycles were analyzed, the stratigraphic layers were subdivided, and the top and bottom of each sand body were interpreted in detail.

[0023] The paleogeography of each sand body was restored by combining the optimal residual thickness method and the impression method, and the possible unloading area of ​​the sand body plane in the paleogeographic map was delineated.

[0024] Based on the sand body reservoir development characteristics of multiple drilling phases, combined with sedimentary facies and logging facies analysis of the study area, a single-well geological model was established, and a multi-well model was obtained based on lithological differences.

[0025] Optionally, the range of the interpretation density for the fine interpretation of the top and bottom of each sand body is ≥50m*50m.

[0026] Optionally, the step of assigning corresponding acoustic and density values ​​to multiple sandstone percentage reservoirs in the multi-well geological model to form a forward model specifically includes:

[0027] In the geological model, sandstone and mudstone are assigned corresponding acoustic and density values ​​to form a preliminary forward model;

[0028] By combining the relationship between seismic facies and sandstone percentage content, the final forward model is determined. The final forward model is then used to perform forward simulation to obtain the seismic data from the forward simulation.

[0029] Optionally, the step of comparing and verifying the actual sandstone thickness of wells involved in the prediction and those not involved with the prediction results to obtain the percentage content of sandstone in the zone specifically includes:

[0030] Based on the paleogeographic map, the plane sand body may unload zone and the seismic facies prediction plane attribute map are coupled to predict the sandstone percentage content map.

[0031] The actual sandstone thickness of wells involved in the prediction and those not involved in the prediction were compared with the prediction results to verify the results. The percentage content of sandstone was predicted using drilling data and forward modeling seismic data.

[0032] This invention provides a forward modeling method for predicting sandstone content based on sedimentary cycles. The method includes: Step S1: collecting three-dimensional post-stack and pre-stack data of the target area; Step S2: obtaining a multi-well geological model based on the three-dimensional post-stack and pre-stack data; Step S3: forming a forward model based on the multi-well geological model; Step S4: obtaining a sandstone percentage content planar map using the forward model; Step S5: verifying and obtaining the zonal sandstone percentage content. This method utilizes continuously sampled seismic information, incorporates well data, and aligns with geological understanding, thus improving prediction accuracy.

[0033] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A flowchart of a forward modeling method for predicting sandstone content based on sedimentary cycle constraints is provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram illustrating the application of small-angle superimposed data to calibrate and synthesize records in a specific embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram illustrating the subdivision of strata (sand bodies) based on rock electrical characteristics in a specific embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the flattened cross-section of the Es layer in a specific embodiment of the present invention;

[0039] Figure 5 This is a three-dimensional schematic diagram of the paleogeography of the Es1② period in a specific embodiment of the present invention;

[0040] Figure 6 This is a schematic diagram of the sedimentary facies of the Es1② sand body in a specific embodiment of the present invention;

[0041] Figure 7 This is a schematic diagram of the Es1② stage sand body development zone in a specific embodiment of the present invention;

[0042] Figure 8 This is a schematic diagram of the Es1 geological model in a specific embodiment of the present invention;

[0043] Figure 9 This is a schematic diagram of the forward cross-section of Es1 in a specific embodiment of the present invention;

[0044] Figure 10 This is a schematic diagram of seismic facies prediction for the Es1② sand body in a specific embodiment of the present invention;

[0045] Figure 11 This is a schematic diagram illustrating the prediction of the percentage content of sandstone in the Es1② sand body in a specific embodiment of the present invention;

[0046] Figure 12 This is a schematic diagram illustrating the matching of prediction results with wells in a specific embodiment of the present invention. Detailed Implementation

[0047] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0048] The terms "comprising" and "having," and any variations thereof, in the specification, embodiments, claims, and drawings of this invention are intended to cover non-exclusive inclusion, such as including a series of steps or units.

[0049] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0050] Example 1

[0051] A forward modeling method for predicting sandstone content based on sedimentary cycle constraints includes:

[0052] Step 1: Collect three-dimensional post-stack and pre-stack seismic data, well logging data, well logging data, and lithological data of the target area to prepare the data.

[0053] Step 2 involves stacking the pre-stack gathering data of the work area at small angles of 3-13°. Stacking seismic data at small angles helps to improve vertical resolution and effectively identify thin and interbedded sand bodies. Fine synthetic record calibration confirms the authenticity of lithological reflections. The vertical resolution of the reservoir is improved by using small-angle seismic data and fine synthetic record calibration.

[0054] Step 3: Based on the rock-electric characteristics, analyze the sedimentary cycles, subdivide the strata (sand groups), and provide a detailed interpretation of the top and bottom of each sand body, with an interpretation density of 50m*50m to ensure the accuracy of seismic interpretation.

[0055] Step 4: Based on Step 3, the paleogeography of each sand body is restored by combining the residual thickness method and the impression method, and the possible unloading area of ​​the sand body plane is delineated in the paleogeographic map.

[0056] Step 5: Based on Step 3, according to the sand body reservoir development characteristics of different drilling stages, combined with the analysis of sedimentary facies and logging facies in the study area, establish a single-well geological model, and then obtain a multi-well model based on lithological differences.

[0057] Step 6: Based on Step 5, assign corresponding acoustic wave and density values ​​to sandstone and mudstone in the geological model to form a preliminary forward model. Then, combine the relationship between seismic facies and sandstone percentage content to clarify the final forward model. Use the final forward model to perform forward simulation to obtain the forward simulation seismic data.

[0058] Step 7: Based on Step 6, extract inter-layer seismic facies attributes from the seismic data obtained by forward modeling and predict the distribution range of different seismic facies.

[0059] Step 8: Based on the paleogeographic map, the plane sand body may unloading zone and the seismic facies prediction plane attribute map are coupled to predict the sandstone percentage content map.

[0060] Step 9: Compare and verify the actual sandstone thickness of wells involved in the prediction and those not involved with the prediction results, and use drilling data and forward modeling seismic data to predict the percentage content of sandstone.

[0061] This invention, under the premise of subdividing units (sand groups) and constrained by paleogeography, employs a forward modeling and seismic attribute method overlay technique to predict the percentage content of sandstone. The advantages of this invention are that it utilizes continuously sampled seismic information, incorporates well data, and aligns with geological understanding, thus improving prediction accuracy.

[0062] This invention first establishes a single-well geological model based on actual drilling, and then performs lithological interpolation based on sedimentary facies analysis to obtain a multi-well geological model. Based on the reservoirs with different sandstone percentages in the geological model, corresponding acoustic and density values ​​are assigned, forming a forward model. The forward model is used to obtain seismic data to predict the distribution range of different seismic facies. Then, combining the relationship between seismic facies and sandstone percentage, a sandstone percentage planar map is obtained. Subsequently, the actual sandstone thickness of wells involved in the prediction and those not involved in the prediction are compared with the prediction results for verification, ultimately obtaining the zonal sandstone percentage. This invention applies exploration deployment to predict sandstone percentage, providing a more reliable prediction of sandstone percentage.

[0063] Example 2

[0064] like Figure 1 As shown, Figure 1 This is a flowchart of a technical method for predicting the percentage content of sandstone based on sedimentary cycles under paleogeographic constraints, according to the present invention.

[0065] Step 101: Collect three-dimensional post-stack and pre-stack seismic data, well logging data, well logging data and lithological data of the target area to prepare the data;

[0066] Step 102 involves small-angle stacking of pre-stack gathering data (3-13°) in the work area. Small-angle stacking of seismic data helps improve vertical resolution, refines synthetic record calibration, and clarifies and confirms the petrophysical characteristics of different lithologies. In one embodiment, the 3D seismic data in the target layer of the study area has a narrow frequency band, low dominant frequency, and low signal-to-noise ratio. By improving the vertical resolution through frequency conversion, the synthetic record wavelet matches the wellbore data more closely, further clarifying and confirming the correspondence between lithology and seismic reflection characteristics. 60% of the sandstone top interface corresponds to strong reflection, such as... Figure 2 As shown.

[0067] Step 103: Through rock-electric characteristics, sedimentary cycles are analyzed, the strata (sand groups) are subdivided, and the top and bottom of each sand body are interpreted in detail, with an interpretation density of 50m*50m to ensure the accuracy of seismic interpretation.

[0068] Based on step 102, through rock-electrical characteristics and sedimentary cycles, the Shahejie Formation in the work area is divided into Es1 and Es3. Es1 exhibits two reverse cycles, corresponding to seismic profiles, with axial continuity that can be systematically traced. Therefore, Es1 is further divided into two phases. A detailed interpretation of the top and bottom of the three sand bodies developed in Es1 and Es3 is then performed, as follows: Figure 3 As shown.

[0069] Step 104: A combination of the residual thickness method and the impression method is preferred to reconstruct the paleogeography of each sand body phase, delineating the possible unloading zones of the sand body plane on the paleogeographic map. In one embodiment, based on step 102, a combination of the residual thickness method and the impression method is preferred for the three sand bodies (e.g., ...). Figure 4 ) Reconstruct the paleogeography of each sand body (e.g.) Figure 5 ), clearly define the gullies, and combine them with the sedimentary facies of the study area (such as Figure 6 ) and well logging facies analysis, delineating the possible unloading zones of sand bodies in each phase on the plane, such as Figure 7 As shown.

[0070] Step 105: Based on the sand body reservoir development characteristics of different drilling stages, combined with the analysis of sedimentary facies and logging facies in the study area, establish a single-well geological model, and then obtain a multi-well model based on lithological differences.

[0071] like Figure 8 As shown, based on step 104, through analysis of the rock-electric and sedimentary facies of the drilled wells, the Es1① sand body in Well Chengzhong 7 is far from the source, located at the fan end, with a low sand-to-situ ratio, thick mudstone interlayers, and moderate to weak seismic reflection characteristics; the Es② sand body is located in the middle of the fan, with a sand-to-situ ratio of 40%, moderate mudstone interlayers, and moderate to strong seismic reflection characteristics; Es3 is located at the fan root, with a high sand-to-situ ratio of 80%, thin mudstone interlayers, and blank seismic reflection characteristics. First, a single-well geological model is established based on the actual drilled wells, and then a multi-well geological model is obtained by analyzing lithological differences based on sedimentary facies analysis.

[0072] Step 106: Based on step 105, assign corresponding acoustic and density values ​​to reservoirs with different sandstone percentages in the geological model to form a forward model. Seismic data is then obtained using forward modeling. In one embodiment, based on logging data from actual drilling, values ​​are assigned to the forward model: acoustic values ​​for sandstone and mudstone are assigned to 81-85 μS / m and 97-103 μS / m, respectively; and density values ​​for sandstone and mudstone are assigned to 2.3-2.5 g / m³ and 2.2-2.3 g / m³, respectively. The forward model is then used for simulation to obtain seismic data, such as... Figure 9 As shown.

[0073] Step 107: Based on step 106, extract inter-layer seismic facies attributes from the seismic data obtained through forward modeling, predict the distribution range of different seismic facies, and clarify the relationship between seismic facies and sandstone percentage content based on step 105. In one embodiment, DSG software is used to extract waveforms of the Es1① sandstone strata and compare them to predict the distribution range of different seismic facies, clarify the relationship between seismic facies and sandstone percentage content, with blank reflections indicating high sandstone content, medium-strong amplitudes indicating medium sandstone content, and weak reflections indicating low sandstone content. Figure 10 As shown.

[0074] Step 108: Based on the paleogeomorphological map, the possible unloading zone of the planar sand body, the predicted seismic facies planar map, and the relationship between seismic facies and sandstone percentage content are coupled to predict the sandstone percentage content map. In one embodiment, based on the paleogeomorphological map, the possible unloading zone of the planar sand body and the predicted seismic facies planar map are overlaid to clarify the sandstone distribution range, and the relationship between seismic facies and sandstone percentage content established in step 107 is applied to predict the sandstone percentage content planar map, such as... Figure 11 As shown.

[0075] Step 109 involves comparing and verifying the actual sandstone thickness from wells involved in the prediction with those from wells not involved in the prediction, and accurately predicting the percentage content of sandstone using drilling data, forward modeling, and seismic facies plane properties. In one embodiment, the 7Es3 sand body in the study area did not participate in the forward modeling, such as... Figure 12 As shown, the sandstone percentage predicted by Es3 seismic attributes matches the actual sandstone thickness in the drilled well with a consistency of over 80%. In terms of effectiveness, this sandstone percentage prediction technology based on sedimentary cycles superimposed with seismic data under paleogeographic constraints builds a good bridge between lithology and seismic propagation velocity. It utilizes continuously sampled seismic information, takes into account well data, and is consistent with geological understanding, thus improving prediction accuracy.

[0076] Beneficial effects: This invention, under the premise of subdividing units (sand groups) and constrained by paleogeography, uses forward modeling and seismic attribute overlay techniques to predict the percentage content of sandstone. The advantage of this method is that it utilizes continuously sampled seismic information, incorporates well data, and aligns with geological understanding, thus improving prediction accuracy.

[0077] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of 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 forward-modeling method for predicting sandstone content based on sedimentary cycles, characterized in that, The prediction method includes: Step S1: Collect 3D post-stack and pre-stack data of the target region; Step S2: Obtain a multi-well geological model based on the three-dimensional post-stack and pre-stack data; Step S3: Generate a forward model based on the multi-well geological model; Step S4: Obtain a planar map of sandstone percentage content using the forward model; Step S5: Compare and verify to obtain the percentage content of sandstone in the zone.

2. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 1, characterized in that, Step S2, obtaining a multi-well geological model based on the three-dimensional post-stack and pre-stack data, specifically includes: A single-well geological model is established based on the three-dimensional post-stack and pre-stack data, and a multi-well geological model is obtained by lithological interpolation based on sedimentary facies analysis.

3. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 1, characterized in that, Step S3: Forming a forward model based on the multi-well geological model specifically includes: Based on the multiple sandstone percentage reservoirs in the multi-well geological model, corresponding acoustic and density values ​​are assigned to form a forward model.

4. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 1, characterized in that, Step S4: Obtaining the sandstone percentage content planar map using the forward model specifically includes: The forward model is used to simulate earthquake data to predict the distribution range of different seismic facies. Then, by combining the relationship between seismic facies and sandstone percentage content, a sandstone percentage content planar map is obtained.

5. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 1, characterized in that, Step S5: Comparative verification to obtain the percentage content of zoned sandstone specifically includes: The actual sandstone thickness of wells involved in the prediction and those not involved in the prediction were compared with the prediction results to verify the percentage content of sandstone in the zone.

6. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 1, characterized in that, The collection of three-dimensional post-stack and pre-stack data of the target region specifically includes: Collect three-dimensional post-stack and pre-stack seismic data, well logging data, well logging data, and lithological data of the target area to prepare the data; The pre-stack gathering data of the work area were processed by overlaying at an angle of 3-13° and then finely synthesized and calibrated.

7. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 2, characterized in that, The process of establishing a single-well geological model based on the three-dimensional post-stack and pre-stack data, and obtaining a multi-well geological model through lithological interpolation based on sedimentary facies analysis, specifically includes: Based on the lithological and electrical characteristics, the sedimentary cycles were analyzed, the stratigraphic layers were subdivided, and the top and bottom of each sand body were interpreted in detail. The paleogeography of each sand body was restored by combining the optimal residual thickness method and the impression method, and the possible unloading area of ​​the sand body plane in the paleogeographic map was delineated. Based on the sand body reservoir development characteristics of multiple drilling phases, combined with sedimentary facies and logging facies analysis of the study area, a single-well geological model was established, and a multi-well model was obtained based on lithological differences.

8. The method for predicting sandstone content based on sedimentary cycle constraints according to claim 7, characterized in that, The range of interpretation density for the detailed interpretation of the top and bottom of each sand body is ≥50m*50m.

9. The method for predicting sandstone content based on forward modeling under sedimentary cycle constraints according to claim 3, characterized in that, The step of assigning corresponding acoustic and density values ​​to multiple sandstone percentage reservoirs in the multi-well geological model to form a forward model specifically includes: In the geological model, sandstone and mudstone are assigned corresponding acoustic and density values ​​to form a preliminary forward model; By combining the relationship between seismic facies and sandstone percentage content, the final forward model is determined. The final forward model is then used to perform forward simulation to obtain the seismic data from the forward simulation.

10. The method for predicting sandstone content based on sedimentary cycle constraints according to claim 5, characterized in that, The comparison and verification of the actual sandstone thickness of wells involved in the prediction and those not involved in the prediction with the prediction results to obtain the percentage content of sandstone in the zone specifically includes: Based on the paleogeographic map, the plane sand body may unload zone and the seismic facies prediction plane attribute map are coupled to predict the sandstone percentage content map. The actual sandstone thickness of wells involved in the prediction and those not involved in the prediction were compared with the prediction results to verify the results. The percentage content of sandstone was predicted using drilling data and forward modeling seismic data.

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