Shale oil reservoir prediction method

Abstract

The invention belongs to the field of geophysical exploration, and particularly relates to a shale oil reservoir prediction method. According to the method, the seismic attribute characteristics of the top trough and the pedal crest of the reservoir development area are utilized, the average trough energy of the top boundary of the target interval of the target area and the average crest energy between the top boundary and the bottom boundary are adopted for reservoir prediction, and the influence of low-impedance mud-removed shale can be eliminated with the phase control concept; meanwhile, an inversion characteristic curve is reconstructed, a characteristic longitudinal wave impedance curve containing longitudinal wave impedance curve characteristics and natural gamma curve characteristics is obtained, an inversion model is constructed for sandstone reservoir inversion, and the problems that the corresponding relation between seismic wave impedance and seismic reflection characteristics is good, but sand shale cannot be effectively recognized, and the reliability of sandstone reservoir inversion is poor are solved. According to the method, the contradiction that natural gamma identification of sand shale is sensitive but cannot be directly obtained from seismic data is overcome, so that the identification precision of the interlayer type shale reservoir can be effectively improved, the influence of low-resistance shale is eliminated, and the relatively accurate thickness of the interlayer type shale reservoir is calculated.

Description

Technical Field

[0001] The invention belongs to the field of geophysical exploration, and in particular relates to a shale oil reservoir prediction method. Background Art

[0002] In recent years, unconventional oil and gas, especially shale oil and gas, have shown a good development trend and become a new growth point for oil and gas reserves. At present, domestic shale oil and gas are divided into two types according to the sedimentary environment: marine shale gas and continental shale oil. Among them, continental shale oil can be divided into three types according to the sedimentary type: interlayer type, mixed type and pure shale. In recent years, these three types of continental shale oil have achieved major breakthroughs.

[0003] Interlayer shale oil is widely developed in a certain area in China, among which Chang 7 Member has a set of extensive mud shale + fine-grained sandstone, which is a typical continental interlayer shale oil. Some domestic oil companies have made major discoveries and have achieved scale-effective development. Continental interlayer shale oil was first proposed and developed on a large scale in China, and there are great technical differences between it and pure shale oil at home and abroad. The main geological characteristics of interlayer shale oil are the coexistence of source and reservoir, the shale layer contains oil as a whole, and thin sandstone or limestone favorable reservoirs capture oil near the source to form oil and gas accumulation sweet spots. Based on the basic characteristics of the Chang 7 Member source accumulation, an oil field evaluates the sweet spot area from four aspects: hydrocarbon generation, reservoir, oil content and engineering mechanical quality, among which reservoir and oil content are the evaluation focuses; in particular, in order to ensure the development benefits, interlayer shale oil is generally developed by long horizontal wells, and drilling along thin sand bodies is required, which has higher requirements for the prediction accuracy of interlayer shale oil reservoirs. Interlayer shale oil generally has interlayers of shale and sandstone, and single sand bodies are relatively thin, generally less than 20m. The difference in wave impedance between sandstone and surrounding rock is small, and sand bodies and mudstone are difficult to effectively distinguish. How to improve the fine accuracy of the reservoir and ensure accurate targeting of horizontal wells is a difficulty faced in the development of interlayer shale oil.

[0004] In the paper "Geological Characteristics and Exploration and Development Progress of Mesozoic Chang 7 Shale Oil in the Ordos Basin", authors Fu Jinhua, Niu Xiaobing and others proposed to use generalized S transform time-frequency analysis technology, multi-attribute fusion and other technologies to improve the ability to identify reservoirs in interlayer shales, and can identify sandstone reservoirs over 8m. This method can perform qualitative analysis on sandstone reservoirs, but the seismic profile obtained is a single-frequency seismic reflection profile, not a stratigraphic profile, and cannot quantitatively analyze the reservoir thickness and vertical boundaries, which cannot meet the requirements of horizontal well development.

[0005] In the paper "Key Scientific and Technological Issues in the Development of Shale Oil Horizontal Wells in the Ordos Basin", Lei Qihong, He Youan and others proposed to use prestack geostatistical inversion technology to improve reservoir resolution, carry out 5m thin reservoir seismic research, and finely characterize the vertical and horizontal distribution of reservoirs to guide target trajectory design. Although this method can effectively identify sandstone in interlayer shale, prestack inversion requires the work area to have relatively complete prestack gather data. The work area has drilled many wells and has complete logging data. It is difficult for old work areas to meet the data requirements of prestack geostatistical inversion.

[0006] In summary, the existing technical means of identifying interlayer shale oil reservoirs are difficult to effectively distinguish sandstone from surrounding rock, sand body from mudstone, resulting in insufficient precision in reservoir identification. It is difficult to meet the requirements of target window accuracy for shale oil horizontal well development, or it has high requirements for seismic and well data in the prediction area, making it difficult to carry out related work in sparse well areas and work areas lacking pre-stack gather seismic data. Summary of the invention

[0007] The purpose of the present invention is to provide a shale oil reservoir prediction method to solve the problem in the prior art that it is difficult to effectively identify sandstone in sparse well areas and work areas lacking pre-stack gather seismic data, resulting in insufficient precision in reservoir identification.

[0008] In order to achieve the above object, the present invention provides a shale oil reservoir prediction method, comprising the following steps:

[0009] 1) performing well-seismic calibration on post-stack seismic data and well logging data of a target area to correspond the post-stack seismic data in the time domain and the well logging data in the depth domain; the target area includes a sandstone lithofacies interval;

[0010] 2) Obtaining the reflection characteristics of the top and bottom boundaries of the reservoir in the target area according to the well seismic calibration results, and determining the thresholds corresponding to the average trough energy of the top boundary of the target layer section in the target area and the average peak energy between the top boundary and the bottom boundary according to the reflection characteristics of the top and bottom boundaries of the known reservoir in the target area;

[0011] 3) Based on the post-stack seismic data and the stratigraphic interpretation data of the top and bottom boundaries of the target layer, the average trough energy of the top boundary of the target layer segment to be predicted and the average peak energy between the top boundary and the bottom boundary are obtained;

[0012] Acquire a characteristic P-wave impedance curve of the target area, and determine a threshold value of the P-wave impedance for sandstone reservoir inversion according to the characteristic P-wave impedance curve;

[0013] An inversion model is constructed based on the characteristic longitudinal wave impedance curve of the target area and the post-stack seismic data to obtain the wave impedance inversion data volume;

[0014] 4) According to the wave impedance inversion data body, the average trough energy of the top boundary of the target layer segment to be predicted in the target area, and the average peak energy between the top boundary and the bottom boundary, the shale oil reservoir at the position to be predicted in the target area is identified; if the average trough energy of the top boundary at a certain position is less than the corresponding threshold, the average peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold, and there is a characteristic longitudinal wave impedance lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir in the wave impedance inversion data body corresponding to the position, it is determined that there is a shale oil reservoir at the position, and the reservoir thickness at the position is calculated according to the number of data sampling points in the wave impedance inversion data body corresponding to the position where the characteristic longitudinal wave impedance is lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir; otherwise, it is determined that there is no shale oil reservoir at the position, and the reservoir thickness at the position is marked as 0.

[0015] The beneficial effects of the above technical solution are: utilizing the seismic attribute characteristics of "trough on top and peak at the bottom" in the reservoir development area, using the average trough energy of the top boundary of the target layer in the target area and the average peak energy between the top boundary and the bottom boundary for reservoir prediction, it is possible to eliminate the influence of low-impedance muddy shale, thereby calculating a more accurate thickness of the favorable interlayer shale reservoir.

[0016] Further, the reservoir thickness at the location where the shale oil reservoir exists is calculated as follows:

[0017] H=n*T*v*0.5

[0018] Among them, H is the reservoir thickness, n is the number of data sampling points below the threshold value of the inversion longitudinal wave impedance of the sandstone reservoir; T is the sampling rate; v is the propagation speed of the seismic wave in the reservoir.

[0019] Furthermore, the characteristic longitudinal wave impedance curve of the target area is obtained by:

[0020] The part of the longitudinal wave impedance curve obtained according to the post-stack seismic data with a frequency less than or equal to the seismic effective frequency band is extracted as the low-frequency part of the characteristic longitudinal wave impedance curve, and the part of the natural gamma curve with a frequency greater than the seismic effective frequency band is extracted as the high-frequency part of the characteristic longitudinal wave impedance curve; the low-frequency part and the high-frequency part are superimposed in the frequency domain to obtain the characteristic longitudinal wave impedance curve of the target area.

[0021] The beneficial effects of the above technical solution are: using the curve reconstruction technology to reconstruct the inversion characteristic curve to obtain a characteristic longitudinal wave impedance curve that contains both the longitudinal wave impedance curve characteristics and the natural gamma curve characteristics, which is used to determine the inversion longitudinal wave impedance threshold value of the sandstone reservoir and to construct an inversion model. It can solve the problems that the longitudinal wave impedance obtained from post-stack seismic data has limited accuracy in identifying sand and mudstone, the natural gamma ray is sensitive to identifying sand and mudstone but cannot be obtained from post-stack seismic data, and the seismic reflection characteristics only have a corresponding relationship with the seismic wave impedance interface, and effectively filter out the parts of the longitudinal wave impedance curve that are not related to the seismic characteristics, thereby effectively improving the prediction accuracy of interlayer shale reservoirs.

[0022] Furthermore, the sandstone reservoir inversion longitudinal wave impedance threshold value is determined as follows:

[0023] Through the intersection analysis of wave impedance and natural gamma of the wells drilled in the target area, the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area is determined respectively, and the inversion longitudinal wave impedance threshold of the sandstone reservoir is determined according to the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of the shale oil reservoir prediction method in the embodiment of the shale oil reservoir prediction method of the present invention;

[0025] Figure 2 It is a schematic diagram of the well seismic calibration results of the target area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0026] Figure 3 This is a schematic diagram of the analysis of distinguishing sandstone and mudstone by using longitudinal wave resistance and natural gamma (GR) in the embodiment of the shale oil reservoir prediction method of the present invention;

[0027] Figure 4 It is a schematic diagram of a characteristic longitudinal wave impedance curve of a target area reconstructed according to a longitudinal wave impedance curve and a natural gamma curve in an embodiment of a shale oil reservoir prediction method of the present invention;

[0028] Figure 5 A schematic diagram of determining a characteristic impedance threshold value by the intersection of characteristic impedance and natural gamma (GR) in an embodiment of a shale oil reservoir prediction method of the present invention;

[0029] Figure 6 The inversion prediction reservoir thickness plane map constructed by using the characteristic longitudinal wave impedance curve of the target area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0030] Figure 7 It is a schematic diagram of the average trough amplitude of the sand body top in the effective sandstone development area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0031] Figure 8 It is a schematic diagram of the average wave peak amplitude of the sand bottom in the effective sandstone development area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0032] Fig. 9 It is a characteristic schematic diagram of the top wave valley and the foot wave peak of the effective sandstone development area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0033] Fig.10a It is a schematic diagram of comparing the sandstone prediction result and the actual logging result of Well A in a certain well area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0034] Fig.10b It is a schematic diagram of comparing the sandstone prediction result and the actual logging result of Well B in a certain well area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0035] Fig.10c It is a schematic diagram of comparing the sandstone prediction result and the actual logging result of Well C in a certain well area in the embodiment of the shale oil reservoir prediction method of the present invention;

[0036] Fig.11 It is a schematic diagram of a shale oil reservoir prediction and its corresponding exploration well results in an embodiment of the shale oil reservoir prediction method of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0038] Shale oil reservoir prediction method embodiment

[0039] This embodiment provides a technical solution for a shale oil reservoir prediction method. Figure 1 , including the following steps:

[0040] 1) Perform well-seismic calibration on the post-stack seismic data and logging data of the target area to correspond the post-stack seismic data in the time domain to the logging data in the depth domain; the target area includes a sandstone lithofacies section. In this embodiment, the prediction of interlayer shale oil reservoirs in the Chang 7 section of the Mesozoic (i.e., the target layer section) in a certain study area (i.e., the target area) is taken as an example to illustrate the technical scheme of the shale oil reservoir prediction method; the target area has a three-dimensional post-stack seismic data body and the top and bottom boundary interpretation layers of each sub-section of the target layer. More than 20 wellheads have been drilled into the target layer, of which 12 wells have natural gamma, acoustic time difference, density and other logging curves and lithology logging profiles. The existing logging curves can be used to calculate the P-wave impedance curve and rock porosity results data. The Chang 7 section in the study area can be divided into three subsections, Chang 71, 72 and 73, in which three types of lithology combinations, mud shale, sandstone and mud-bearing sandstone, are mainly developed. The reservoir is mainly developed in the Chang 72 subsection. In the existing technology, the dense mud-bearing sandstone is mainly eliminated by the longitudinal wave impedance value, but the longitudinal wave impedance is ineffective in distinguishing mud shale and sandstone.

[0041] like Figure 2 The figure shows the well-seismic calibration results of the target area. Since the well logging data is depth domain data and the post-stack seismic data is time domain data, the two need to be matched with each other so as to analyze the reflection characteristics of the top and bottom boundaries of the reservoir in the target area by combining the post-stack seismic data and the well logging data.

[0042] 2) Obtain the reflection characteristics of the top and bottom boundaries of the known reservoirs in the target area according to the well-seismic calibration results, and determine the thresholds corresponding to the average trough energy of the top boundary of the target layer section in the target area and the average peak energy between the top boundary and the bottom boundary according to the reflection characteristics of the top and bottom boundaries of the known reservoirs in the target area;

[0043] Reference Figure 2 , the target layer (i.e., the 7th segment of the Biogeosphere, corresponding to Figure 2 The top boundary position of the sand body (i.e., the sandstone reservoir part) in the layer section between chang7 and chang6 is shown as the position marked by sand t, and the bottom boundary position is shown as the position marked by sand b. It can be seen that the reflection characteristics of the top and bottom boundaries of the reservoir in the target area can prove that the sandstone reservoir is developed between the trough and the crest, forming a seismic reflection characteristic of "trough on top and crest on the bottom", while the reservoir in the low-resistance mudstone development area and the tight mud-bearing sandstone development area do not have this seismic reflection characteristic. Therefore, by using the seismic attribute characteristics of "trough on top and crest on the bottom" in the reservoir development area, the average trough energy of the top boundary of the target layer section in the target area (abbreviated as attribute parameter a in this embodiment) and the average crest energy between the top boundary and the bottom boundary (abbreviated as attribute parameter b in this embodiment) are used for reservoir prediction to eliminate the influence of low-impedance de-mud shale, thereby calculating a more accurate thickness of the favorable interlayer shale reservoir.

[0044] Since the average trough energy of the top boundary of the target layer section reservoir in the known target area and the average peak energy between the top boundary and the bottom boundary (that is, the value of the attribute parameter a and the value of the attribute parameter b corresponding to the known target layer section reservoir in the target area) are directly taken as the threshold for identifying reservoirs at other positions in the target layer section in the target area, there may be errors in the calculation results of the values ​​of the attribute parameters a and b of the target layer section in the target area due to the influence of other factors, resulting in missed detection. Therefore, in this embodiment, the thresholds corresponding to the attribute parameters a and b are respectively taken to be smaller than the values ​​of the attribute parameters A and B corresponding to the known target layer section reservoir in the target area. The threshold can be selected according to the actual well-seismic calibration results of the target layer section in the target area. For example, for the Chang 72 subsection in this embodiment, the thresholds corresponding to the selected attribute parameters a and b are -100 and 100, respectively.

[0045] 3) Based on the post-stack seismic data and the stratigraphic interpretation data of the top and bottom boundaries of the target layer, the average trough energy of the top boundary of each position in the target layer segment to be predicted and the average peak energy between the top boundary and the bottom boundary are obtained;

[0046] The characteristic P-wave impedance curve of the target area is obtained, and the P-wave impedance threshold of the sandstone reservoir inversion is determined according to the characteristic P-wave impedance curve. An inversion model is constructed according to the characteristic P-wave impedance curve of the target area and the post-stack seismic data, and the wave impedance inversion data volume is obtained through waveform indication inversion.

[0047] In this embodiment, considering that the longitudinal wave impedance in the target area has limited accuracy in identifying sand and mudstone, Figure 3 As shown in the figure, although GR (natural gamma) is more sensitive in identifying sand and mudstone, post-stack seismic inversion can only obtain P-wave impedance data, and the seismic reflection characteristics only correspond to the seismic wave impedance interface; therefore, in order to improve the identification accuracy of interlayer shale reservoirs, the curve reconstruction technology is used to reconstruct the inversion "characteristic curve" to obtain the characteristic P-wave impedance curve of the target area, which is used to determine the P-wave impedance threshold value of the sandstone reservoir inversion and to build the inversion model. The specific reconstruction method is as follows:

[0048] Extract the part of the P-wave impedance curve obtained from the post-stack seismic data with a frequency less than or equal to the effective seismic frequency band as the low-frequency part of the characteristic P-wave impedance curve, and extract the part of the natural gamma curve with a frequency greater than the effective seismic frequency band as the high-frequency part of the characteristic P-wave impedance curve; superimpose the low-frequency part and the high-frequency part in the frequency domain to obtain the characteristic P-wave impedance curve of the target area. In this embodiment, the maximum effective seismic frequency band is 55 Hz, which means that the parts of the P-wave impedance curve greater than 55 Hz are all irrelevant to the seismic reflection characteristics, so refer to Figure 4, select the part below 55Hz in the longitudinal wave impedance curve as the low-frequency part, which is used to correspond to the pre-stack seismic data, and the part above 55Hz in the GR curve as the high-frequency part, which is used to distinguish lithology (distinguishing sandstone and mudstone); superimpose the two in the frequency domain to reconstruct the following Figure 4 The characteristic longitudinal wave impedance curve of the target area is shown in the figure. The inversion model constructed using this curve can not only establish a conversion relationship with the seismic profile, but also eliminate the influence of sandstone and mudstone. Compared with conventional seismic inversion methods, it can effectively improve the reservoir identification resolution and prediction accuracy.

[0049] The specific method for determining the threshold value of the inversion longitudinal wave impedance of sandstone reservoir is as follows:

[0050] Through the intersection analysis of wave impedance and natural gamma of the wells drilled in the target area ( Figure 5 As shown in FIG. 1 ), the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area is determined respectively, and the inversion longitudinal wave impedance threshold value of the sandstone reservoir is determined according to the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area. In this embodiment, Figure 5 As shown in the figure, the horizontal axis is the GR value, and the vertical axis is the P-wave impedance value; the circled range in the figure represents the reservoir, the points enclosed in the circle are the GR and P-wave impedance value points corresponding to sandstone (referred to as sandstone points), and the rest are the GR and P-wave impedance value points corresponding to non-sandstone (referred to as non-sandstone points); Figure 5 It can be seen that the longitudinal wave impedance value of the sandstone point and the non-sandstone point is 10800g / cm 3 *m / s, then the rock physics intersection analysis is used, and the new characteristic curve of 10800g / cm 3 *m / s can be used as the threshold value to effectively distinguish sandstone; therefore, the threshold value of the inversion P-wave impedance of the sandstone reservoir determined by the characteristic P-wave impedance curve is 10800g / cm 3 *m / s, which is the threshold range for distinguishing low-resistance reservoirs from surrounding rocks (high-resistance sandstone and mudstone).

[0051] 4) According to the wave impedance inversion data body, the average trough energy of the top boundary of the target layer segment to be predicted in the target area, and the average peak energy between the top boundary and the bottom boundary, the shale oil reservoir in the target area is identified; if the average trough energy of the top boundary of a certain position in the target layer segment of the target area is less than the corresponding threshold, the average peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold, and there is a characteristic longitudinal wave impedance lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir in the wave impedance inversion data body corresponding to the position, then it is determined that there is a shale oil reservoir at this position, and the reservoir thickness at this position is calculated according to the number of data sampling points in the wave impedance inversion data body corresponding to the position where the characteristic longitudinal wave impedance is lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir; otherwise, it is determined that there is no shale oil reservoir at this position, and the reservoir thickness at this position is marked as 0.

[0052] Since sandstone and mudstone overlap in the study area and both have low P-wave impedance, it is impossible to distinguish sandstone using P-wave impedance alone. However, the effective sandstone development area has the reflection characteristics of “wave troughs on the top and wave crests on the feet”, e.g. Figure 7 , Figure 8 , Fig. 9 As shown, according to the above analysis results, the interlayer shale oil favorable reservoir in the target layer section (Chang 72 subsection) of the target area of ​​this embodiment meets the following three conditions:

[0053] (1) The inversion feature exists in the wave impedance inversion data volume. The longitudinal wave impedance is lower than 10800 g / cm 3 *m / s;

[0054] (2) The average trough energy of the top boundary is less than -100;

[0055] (3) The average peak energy within the layer between the top and bottom boundaries is greater than 100.

[0056] For the convenience of representation, the average trough energy of the top boundary of each predicted position in the target layer of the target area is recorded as seismic attribute layer data A, the average peak energy between the top boundary and the bottom boundary is recorded as seismic attribute layer data B, and the wave impedance inversion data body obtained according to the characteristic longitudinal wave impedance curve of the target area and the post-stack seismic data is recorded as seismic attribute layer data C; the following logical operation relationship is constructed to predict the shale oil reservoir:

[0057] If either of the two conditions that A is less than -100 and B is greater than 100 is not met, the reservoir thickness H at the coordinate point corresponding to the position is assigned a value of 0.

[0058] If A is less than -100 and B is greater than 100, both conditions are met, then the inversion data volume C at this coordinate point that satisfies the characteristic longitudinal wave impedance is less than 10800g / cm 3 *m / s data sampling points and calculate the reservoir thickness at that location to predict the reservoir thickness and assign it to the layer data H under that coordinate point.

[0059] The method for calculating the reservoir thickness at the location where the shale oil reservoir exists is as follows:

[0060] H=n*T*v*0.5

[0061] Among them, H is the reservoir thickness, n is the number of data sampling points below the inversion longitudinal wave impedance threshold of the sandstone reservoir; T is the sampling rate; v is the reservoir velocity, that is, the propagation speed of seismic waves in the reservoir. Since the interlayer shale oil reservoir is sandstone, the reservoir velocity of the sandstone in the study area where the target area is located is generally between 4000-4600m / s, so the reservoir velocity here is taken as 4500m / s.

[0062] In this embodiment, the final calculation result of the shale oil reservoir thickness is as follows: Figure 6 As shown, the calculation results are much more accurate than those of conventional inversion methods and are more consistent with geological laws. Figure 10a-10c There are three verification wells in the study area; Fig.10a This is a schematic diagram comparing the sandstone prediction results and the actual logging results of Well A in the well area. Fig.10b This is a schematic diagram comparing the sandstone prediction results and the actual logging results of Well B in the well area. Fig.10c This is a schematic diagram comparing the sandstone prediction results and the actual logging results of Well C in the well area. The gray part is the predicted high-quality reservoir development part, and the part between the dotted lines is the sandstone area, that is, the reservoir location. Fig.10a The predicted reservoir position is 608m-629.5m, while the reservoir position obtained from the actual well is 607m-628m; Fig.10b , Fig.10c Similarly, it can be seen that compared with the conventional inversion method, the prediction accuracy of this method is greatly improved. The inversion result is basically consistent with the logging result, and the error is basically less than or equal to 2m. Therefore, the prediction result can provide a basis for horizontal well targeting.

[0063] The results of a new drilling well corresponding to a certain prediction are as follows Fig.11 As shown in the figure, the grey part is the predicted high-quality reservoir development section; from the analysis of the three oil and gas layer evaluation factors of oil layer classification, oil content and porosity, the first-class reservoirs, oil layers with oil content greater than 45% and good oil layers with porosity greater than 8% in the newly drilled horizontal wells are all located in the predicted high-quality reservoir development section, and the actual drilling results are consistent with the seismic inversion prediction, which confirms that the application effect of the shale oil reservoir prediction method for interlayer shale oil sweet spots in this embodiment is better. In summary, the shale oil reservoir prediction method of this embodiment adopts two seismic sensitive attributes, namely the top average trough energy and the interlayer average peak energy, based on the seismic reflection characteristics of the reservoir head trough and foot peak, to achieve inversion and reserve determination and attribute control, thereby improving the prediction accuracy of shale oil reservoirs. Therefore, it is possible to identify thin oil reservoirs and improve the prediction level of sweet spots in interlayer shale areas. In addition, this method does not require the use of a large amount of prestack seismic data and massive well data, so it is more suitable for reservoir sweet spot prediction in areas without prestack seismic data and sparse well networks. In view of the problem that sandstone and mudstone are difficult to distinguish in the prediction process of interlayer shale oil reservoirs, the curve reconstruction + waveform indication inversion method is used to maintain the characteristics of the seismic itself while improving the thin reservoir identification capability.

[0064] The present invention has the following characteristics:

[0065] 1) By utilizing the seismic attribute characteristics of "wave trough on top and wave crest on bottom" in the reservoir development area, the average wave trough energy at the top boundary of the target layer in the target area and the average wave crest energy between the top boundary and the bottom boundary are used for reservoir prediction, which can eliminate the influence of low-impedance muddy shale, thereby calculating a more accurate thickness of the favorable interlayer shale reservoir.

[0066] 2) Since the P-wave impedance in the target area has limited accuracy in identifying sand and mudstone, and although natural gamma ray is more sensitive in identifying sand and mudstone, post-stack seismic inversion can only obtain P-wave impedance data, and the seismic reflection characteristics only correspond to the seismic wave impedance interface; therefore, the curve reconstruction technology is used to reconstruct the inversion "characteristic curve" to obtain the characteristic P-wave impedance curve of the target area that contains both the P-wave impedance curve characteristics and the natural gamma ray curve characteristics. This is used to determine the P-wave impedance threshold value for sandstone reservoir inversion and to construct an inversion model, which can effectively improve the identification accuracy of interlayer shale reservoirs.

[0067] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, but do not constitute a limitation to the present invention.

Claims

1. A shale oil reservoir prediction method, characterized in that: The steps include: 1) performing well-seismic calibration on post-stack seismic data and well logging data of a target area to correspond the post-stack seismic data in the time domain and the well logging data in the depth domain; the target area includes a sandstone lithofacies interval; 2) Obtaining the reflection characteristics of the top and bottom boundaries of the reservoir in the target area according to the well seismic calibration results, and determining the thresholds corresponding to the average trough energy of the top boundary of the target layer section in the target area and the average peak energy between the top boundary and the bottom boundary according to the reflection characteristics of the top and bottom boundaries of the known reservoir in the target area; 3) Based on the post-stack seismic data and the stratigraphic interpretation data of the top and bottom boundaries of the target layer, the average trough energy of the top boundary of the target layer segment to be predicted and the average peak energy between the top boundary and the bottom boundary are obtained; Acquire a characteristic P-wave impedance curve of the target area, and determine a threshold value of the P-wave impedance for sandstone reservoir inversion according to the characteristic P-wave impedance curve; An inversion model is constructed based on the characteristic longitudinal wave impedance curve of the target area and the post-stack seismic data to obtain the wave impedance inversion data volume; 4) According to the wave impedance inversion data body, the average trough energy of the top boundary of the target layer segment to be predicted in the target area, and the average peak energy between the top boundary and the bottom boundary, the shale oil reservoir at the position to be predicted in the target area is identified; if the average trough energy of the top boundary at a certain position is less than the corresponding threshold, the average peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold, and there is a characteristic longitudinal wave impedance lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir in the wave impedance inversion data body corresponding to the position, it is determined that there is a shale oil reservoir at the position, and the reservoir thickness at the position is calculated according to the number of data sampling points in the wave impedance inversion data body corresponding to the position where the characteristic longitudinal wave impedance is lower than the inversion longitudinal wave impedance threshold value of the sandstone reservoir; otherwise, it is determined that there is no shale oil reservoir at the position, and the reservoir thickness at the position is marked as 0.

2. The shale oil reservoir prediction method according to claim 1, characterized in that: The reservoir thickness at locations where shale oil reservoirs exist is calculated as follows: H=n*T*v*0.5 Among them, H is the reservoir thickness, n is the number of data sampling points below the threshold value of the inversion longitudinal wave impedance of the sandstone reservoir; T is the sampling rate; v is the propagation speed of the seismic wave in the reservoir.

3. The shale oil reservoir prediction method according to claim 1 or 2, characterized in that: The characteristic longitudinal wave impedance curve of the target area is obtained as follows: The part of the longitudinal wave impedance curve obtained according to the post-stack seismic data with a frequency less than or equal to the seismic effective frequency band is extracted as the low-frequency part of the characteristic longitudinal wave impedance curve, and the part of the natural gamma curve with a frequency greater than the seismic effective frequency band is extracted as the high-frequency part of the characteristic longitudinal wave impedance curve; the low-frequency part and the high-frequency part are superimposed in the frequency domain to obtain the characteristic longitudinal wave impedance curve of the target area.

4. The shale oil reservoir prediction method according to claim 1 or 2, characterized in that: The determination method of the inversion longitudinal wave impedance threshold value of the sandstone reservoir is as follows: Through the intersection analysis of wave impedance and natural gamma of the drilled wells in the target area, the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area is determined respectively, and the inversion longitudinal wave impedance threshold of the sandstone reservoir is determined according to the inversion longitudinal wave impedance range of the sandstone reservoir and the non-sandstone surrounding rock in the target area.

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