A method for predicting shale oil reservoirs

Abstract

The present application belongs to the field of geophysical exploration, and particularly relates to a shale oil reservoir prediction method. The present application uses the seismic attribute characteristics of the "head wave valley, foot wave peak" of the reservoir development area, adopts the average wave valley energy of the top boundary of the target area target layer and the average wave peak energy between the top boundary and the bottom boundary for reservoir prediction, and the phase control concept can eliminate the influence of low impedance mud shale; meanwhile, the inversion characteristic curve is reconstructed to obtain the characteristic longitudinal wave impedance curve containing the characteristics of longitudinal wave impedance curve and natural gamma curve, and the inversion model is constructed for sandstone reservoir inversion, solving the contradiction that the seismic wave impedance and the seismic reflection characteristics have good corresponding relationship, but cannot effectively identify sand shale, and the natural gamma can identify sand shale, but cannot be directly obtained from the seismic data, so that the identification accuracy of the interbedded shale reservoir can be effectively improved, the influence of low resistance mud shale can be eliminated, and the thickness of the interbedded shale reservoir can be calculated more accurately.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of geophysical exploration, and particularly relates to a shale oil reservoir prediction method. BACKGROUND

[0002] In recent years, unconventional oil and gas, especially shale oil and gas, has shown a good development trend and become a new growth point for oil and gas reserves. At present, domestic shale oil and gas is divided into marine shale gas and continental shale oil according to the sedimentary environment, among which continental shale oil can be divided into interbedded type, mixed type and pure shale type according to the sedimentary type. In recent years, all of the three types of continental shale oil have achieved major breakthroughs.

[0003] Interbedded shale oil is widely developed in a certain area in China, and a set of widely covered mud shale + fine-grained sandstone is deposited in the Chang 7 member, which is a typical continental interbedded shale oil. Some domestic oil companies have made major discoveries and have realized scale benefit development. Continental interbedded shale oil is first proposed in China and realized scale development, which has great difference with the pure shale type shale oil at home and abroad. The main geological characteristics of interbedded shale oil are that source and reservoir coexist, the shale series as a whole contains oil, and the thin sandstone or limestone near the source captures oil to form an oil and gas accumulation sweet spot. According to the basic characteristics of source accumulation in the Chang 7 member, a certain oilfield carries out evaluation of the sweet spot area from four aspects of hydrocarbon generation, reservoir, oiliness and engineering mechanics quality, among which the reservoir and oiliness are the evaluation focus. Especially for interbedded shale oil, in order to ensure development benefit, long horizontal section horizontal well development is generally adopted, and the drilling needs to drill along the thin sand body, so higher accuracy is required for the prediction of interbedded shale oil reservoir. The interbedded shale oil is generally interbedded with shale and sandstone, and the single sand body is thinner, generally less than 20m. The wave impedance difference between sandstone and surrounding rock is small, and the sand body and mud shale are difficult to effectively distinguish. How to improve the fine accuracy of the reservoir and ensure the accurate targeting of horizontal wells is a difficulty faced by interbedded shale oil development.

[0004] The paper "Geological characteristics and exploration and development progress of Mesozoic Chang 7 member shale oil in Ordos Basin" published by the authors Fu Jinhua, Niu Xiaobing and others proposes to use generalized S transform time-frequency analysis technology and multi-attribute fusion technology to improve the reservoir identification ability of interbedded shale, which can identify sandstone reservoirs with a thickness of more than 8m. This method can qualitatively analyze the sandstone reservoir, but the obtained seismic section is a single frequency seismic reflection section, not a stratigraphic section, which cannot quantitatively analyze the reservoir thickness and reservoir vertical boundary, and cannot meet the requirements of horizontal well development.

[0005] The authors of the paper "Key technology problems of shale oil horizontal well development in Ordos Basin" Lei Qihong, He Youan, etc. proposed using pre-stack geostatistical inversion technology to improve reservoir resolution, carrying out 5m thin reservoir seismic research, and finely depicting the vertical and horizontal distribution of reservoirs to guide target trajectory design. Although this method can effectively identify sandstone in interbedded shale, pre-stack inversion requires a relatively complete pre-stack gather data in the work area, and the work area has many drilled wells and complete well logging data. It is difficult to meet the data requirements of pre-stack geostatistical inversion in old work areas.

[0006] In summary, the existing technical means for identifying interbedded shale oil reservoirs cannot effectively distinguish between sandstone and surrounding rock, sand body and mud shale, resulting in insufficient fine degree of reservoir identification, which cannot meet the requirements of shale oil horizontal well development for target window accuracy, or requires high 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

[0007] The purpose of the present application is to provide a shale oil reservoir prediction method to solve the problem of insufficient fine degree of reservoir identification due to ineffective identification of sandstone in sparse well areas and work areas lacking pre-stack gather seismic data in the prior art.

[0008] To achieve the above purpose, the present application provides a shale oil reservoir prediction method, comprising the following steps:

[0009] 1) Calibrate the post-stack seismic data and logging data of the target area to correspond to each other in the time domain and depth domain, respectively, to obtain the average wave trough energy of the top boundary of the target area and the average wave peak energy between the top boundary and the bottom boundary of the target area;

[0010] 2) According to the well-seismic calibration results, obtain the top boundary and bottom boundary reflection characteristics of the target area reservoir, and determine the average wave trough energy of the top boundary of the target area and the average wave peak energy corresponding to the threshold value between the top boundary and the bottom boundary according to the top boundary and bottom boundary reflection characteristics of the known reservoir in the target area;

[0011] 3) According to the post-stack seismic data and the top boundary and bottom boundary stratigraphic interpretation data of the target layer, obtain the average wave trough energy of the top boundary of the target layer and the average wave peak energy between the top boundary and the bottom boundary;

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

[0013] Construct an inversion model according to the characteristic P-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 wave trough energy of the top boundary of the target area target layer section to be predicted position and the average wave peak energy between the top boundary and the bottom boundary, shale oil reservoirs in the target area to be predicted position are identified; if the average wave trough energy of the top boundary of a position is less than the corresponding threshold value, the average wave peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold value, and the characteristic compressional wave impedance in the wave impedance inversion data body corresponding to the position is lower than the sandstone reservoir inversion compressional wave impedance threshold value, it is determined that the position exists shale oil reservoir, and the reservoir thickness of the position is calculated according to the number of data sampling points in the wave impedance inversion data body corresponding to the position, which is lower than the sandstone reservoir inversion compressional wave impedance threshold value; otherwise, it is determined that the position does not exist shale oil reservoir, and the reservoir thickness of the position is marked as 0.

[0015] The beneficial effects of the above technical solution are: using the seismic attribute characteristics of the reservoir development area "head wave trough, foot wave peak", using the average wave trough energy of the top boundary of the target area target layer section and the average wave peak energy between the top boundary and the bottom boundary for reservoir prediction, which can eliminate the influence of low impedance de-mud shale, so as to calculate the thickness of the interbedded shale favorable reservoir more accurately.

[0016] Further, the way to calculate the reservoir thickness of the position where shale oil reservoir exists is as follows:

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

[0018] Wherein, H is the reservoir thickness, n is the number of data sampling points lower than the sandstone reservoir inversion compressional wave impedance threshold value; T is the sampling rate; v is the propagation velocity of seismic wave in the reservoir.

[0019] Further, the way to obtain the characteristic compressional wave impedance curve of the target area is as follows:

[0020] Extract the part of the compressional wave impedance curve obtained from the post-stack seismic data, whose frequency is less than or equal to the seismic effective frequency band, as the low frequency part of the characteristic compressional wave impedance curve, and extract the part of the natural gamma curve, whose frequency is greater than the seismic effective frequency band, as the high frequency part of the characteristic compressional wave impedance curve; superimpose the low frequency part and the high frequency part in the frequency domain to obtain the characteristic compressional wave impedance curve of the target area.

[0021] The beneficial effects of the above technical scheme are as follows: the characteristic P-wave impedance curve containing both P-wave impedance curve characteristics and natural gamma curve characteristics is obtained by using the curve reconstruction technology to reconstruct the inversion characteristic curve, is used to determine the sandstone reservoir inversion P-wave impedance threshold value and construct an inversion model, can solve the problem that the P-wave impedance obtained from the post-stack seismic data has limited accuracy in identifying sand and mudstone, the natural gamma is sensitive to the identification of sand and mudstone but cannot be obtained from the post-stack seismic data, and the seismic reflection characteristics only have a corresponding relationship with the seismic wave impedance interface, and effectively filters the part of the P-wave impedance curve that is irrelevant to the seismic characteristics, thereby effectively improving the prediction accuracy of the interbedded shale reservoir.

[0022] Further, the determination manner of the sandstone reservoir inversion P-wave impedance threshold value is as follows:

[0023] The inversion P-wave impedance ranges of the sandstone reservoir and the non-sandstone surrounding rock in the region where the target area is located are determined through the wave impedance and natural gamma intersection analysis of the drilled wells in the target area, and the sandstone reservoir inversion P-wave impedance threshold value is determined according to the inversion P-wave impedance ranges of the sandstone reservoir and the non-sandstone surrounding rock in the region where the target area is located. BRIEF DESCRIPTION OF DRAWINGS

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

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

[0026] Figure 3 It is an analysis schematic diagram of the P-wave impedance and natural gamma (GR) for distinguishing sand and mudstone in the shale oil reservoir prediction method embodiment of the present application;

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

[0028] Figure 5 It is a schematic diagram of the characteristic impedance and natural gamma (GR) intersection for determining the characteristic impedance threshold value in the shale oil reservoir prediction method embodiment of the present application;

[0029] Figure 6 It is an inversion prediction reservoir thickness planar diagram constructed by using the characteristic P-wave impedance curve of the target area in the shale oil reservoir prediction method embodiment of the present application;

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

[0031] Figure 8 Figure 1 is a schematic diagram of average peak amplitude of sand bottom in effective sandstone development area in the shale oil reservoir prediction method embodiment of the present application;

[0032] Figure 9 Figure 2 is a schematic diagram of characteristics of head-over-wave valley and foot-on-wave peak in the effective sandstone development area in the shale oil reservoir prediction method embodiment of the present application;

[0033] Figure 10a Figure 3 is a schematic diagram of comparison between sandstone prediction result and actual logging result of well A in a certain well area in the shale oil reservoir prediction method embodiment of the present application;

[0034] Figure 10b Figure 4 is a schematic diagram of comparison between sandstone prediction result and actual logging result of well B in a certain well area in the shale oil reservoir prediction method embodiment of the present application;

[0035] Figure 10c Figure 5 is a schematic diagram of comparison between sandstone prediction result and actual logging result of well C in a certain well area in the shale oil reservoir prediction method embodiment of the present application;

[0036] Figure 11 Figure 6 is a schematic diagram of shale oil reservoir prediction and corresponding exploration well result in a certain time in the shale oil reservoir prediction method embodiment of the present application. DETAILED DESCRIPTION

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

[0038] Shale oil reservoir prediction method embodiment

[0039] The present embodiment gives a technical scheme of shale oil reservoir prediction method, referring to Figure 1 , including the following steps:

[0040] 1) calibrate the post-stack seismic data and the logging data of the target area to correspond to each other in the time domain and the depth domain, so as to analyze the top boundary and bottom boundary reflection characteristics of the reservoir in the target area by combining the post-stack seismic data and the logging data; the target area contains a sandstone lithofacies section, and in this embodiment, the prediction of the interbedded shale oil reservoir in the Chang 7 section (i.e., the target layer section) of the Mesozoic in a certain research 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 horizons of each sub-section of the target layer, and there are more than 20 wellheads of the wells drilled into the target layer, of which 12 wells have the logging curves of natural gamma, acoustic time difference, density and the like and the lithology logging profile, and the longitudinal wave impedance curve and the rock porosity data can be obtained by calculation using the existing logging curves. The Chang 7 section in the research area can be divided into three sub-sections, i.e., Chang 71, Chang 72 and Chang 73, and the three lithology combinations of mud shale, sandstone and mud-containing sandstone are mainly developed therein, and the reservoir is mainly developed in the Chang 72 sub-section; in the prior art, the dense mud-containing sandstone is eliminated mainly by the longitudinal wave impedance value, but the mud shale and the sandstone cannot be effectively distinguished by the longitudinal wave impedance.

[0041] As shown in Figure 2 , it is the well-seismic calibration result of the target area, and since the logging data is in the depth domain and the post-stack seismic data is in the time domain, the two need to be corresponded to each other so as to analyze the top boundary and bottom boundary reflection characteristics of the reservoir in the target area by combining the post-stack seismic data and the logging data.

[0042] 2) obtain the top boundary and bottom boundary reflection characteristics of the known reservoir in the target area according to the well-seismic calibration result, and determine the threshold corresponding to the average wave trough energy of the top boundary of the target layer section and the average wave peak energy between the top boundary and the bottom boundary of the target layer section, respectively;

[0043] Referring to Figure 2 , the top boundary position of the sand body (i.e., the sandstone reservoir part) in the target layer section (i.e., the Chang 7 section of the Mesozoic, corresponding to the section between chang7 and chang6 in Figure 2 ) is shown as a position marked by sand t, and the bottom boundary position is shown as a position marked by sand b, so it can be seen that the top boundary and bottom boundary reflection characteristics of the reservoir in the target area can prove that the sandstone reservoir is developed between the wave trough and the wave peak to form the seismic reflection characteristics of "head over wave trough and foot on wave peak", and the reservoir in the low-resistance mudstone development area and the dense mud-containing sandstone development area does not have such seismic reflection characteristics, so the influence of the low-resistance mudstone can be eliminated by using the seismic attribute characteristics of "head over wave trough and foot on wave peak" of the reservoir development area and using the average wave trough energy of the top boundary of the target layer section (referred to as attribute parameter a in this embodiment) and the average wave peak energy between the top boundary and the bottom boundary of the target layer section (referred to as attribute parameter b in this embodiment) to predict the reservoir, so that the relatively accurate thickness of the interbedded shale favorable reservoir can be calculated.

[0044] Since the average trough energy of the top boundary of the reservoir of the known target area target interval and the average peak energy between the top boundary and the bottom boundary (i.e., the values of the attribute parameter a and the attribute parameter b corresponding to the known target area target interval reservoir) are directly taken as the threshold for identifying the reservoir at other locations of the target area target interval, there may be errors in the calculation results of the values of the attribute parameters a and b of the target area target interval due to other factors, resulting in missed detection. Therefore, in the embodiment, the threshold values corresponding to the attribute parameters a and b are less than the values of the attribute parameters A and B corresponding to the known target area target interval reservoir, respectively. The threshold values can be selected according to the actual well-seismic calibration results of the target area target interval. For example, for the long 72 sub-interval in the embodiment, the selected threshold values corresponding to the attribute parameters a and b are -100 and 100, respectively.

[0045] 3) Obtain the average trough energy of the top boundary and the average peak energy between the top boundary and the bottom boundary at each location of the target area target interval to be predicted according to the post-stack seismic data and the top boundary and bottom boundary stratum interpretation data of the target interval;

[0046] Obtain the characteristic P-wave impedance curve of the target area, determine the sandstone reservoir inversion P-wave impedance threshold value according to the characteristic P-wave impedance curve, and construct an inversion model according to the characteristic P-wave impedance curve of the target area and the post-stack seismic data. The wave impedance inversion data volume is obtained by waveform indication inversion.

[0047] In the embodiment, since the P-wave wave impedance in the target area has limited accuracy for identifying sand and shale, as shown in Figure 3 Although GR (natural gamma) is sensitive to identifying sand and shale, post-stack seismic inversion can only obtain P-wave impedance data, and the seismic reflection characteristics only have a corresponding relationship with the seismic wave impedance interface. Therefore, in order to improve the identification accuracy of the interbedded shale reservoir, 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 sandstone reservoir inversion P-wave impedance threshold value and construct an inversion model. The specific reconstruction method is as follows:

[0048] Extract the part with a frequency less than or equal to the seismic effective frequency band in the P-wave impedance curve obtained according to the post-stack seismic data as the low-frequency part of the characteristic P-wave impedance curve, and extract the part with a frequency greater than the seismic effective frequency band in the natural gamma curve as the high-frequency part of the characteristic P-wave impedance curve. The low-frequency part and the high-frequency part are superimposed in the frequency domain to obtain the characteristic P-wave impedance curve of the target area. In the embodiment, the seismic effective maximum frequency band is 55 Hz, which means that the part greater than 55 Hz in the P-wave impedance curve is irrelevant to the seismic reflection characteristics. Therefore, with reference to Figure 4, the part below 55Hz in the longitudinal wave impedance curve is selected as the low frequency part for corresponding to the pre-stack seismic data, and the part above 55Hz in the GR curve is selected as the high frequency part for distinguishing lithology (distinguishing sandstone and mudstone); the two are superimposed in the frequency domain to reconstruct the characteristic longitudinal wave impedance curve of the target area as shown in Figure 4 The inversion model constructed by using the curve can establish a conversion relationship with the seismic profile and can eliminate the influence of sandstone and mudstone, and can effectively improve the reservoir identification resolution and prediction accuracy compared with the conventional seismic inversion method.

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

[0050] The sandstone reservoir inversion longitudinal wave impedance range of the target area is determined by the wave impedance and natural gamma cross analysis of the drilled wells in the target area as shown in Figure 5 The sandstone reservoir inversion longitudinal wave impedance range of the target area is determined by the wave impedance and natural gamma cross analysis of the drilled wells in the target area as shown in Figure 5 The specific way for determining the sandstone reservoir inversion longitudinal wave impedance threshold value is as follows: Figure 5 It can be seen from 3 that the sandstone points and the non-sandstone points intersect at the longitudinal wave impedance value of 10800 g / cm 3 *m / s, then 10800 g / cm 3 *m / s in the new characteristic curve as the threshold value can effectively distinguish sandstone by using the rock physical cross analysis; thus, the sandstone reservoir inversion longitudinal wave impedance threshold value determined according to the characteristic longitudinal wave impedance curve is 10800 g / cm

[0051] 4) The shale oil reservoir in the target area is identified according to the wave impedance inversion data body, the average wave trough energy of the top boundary of the target area purpose layer segment to be predicted, and the average wave peak energy between the top boundary and the bottom boundary; if the average wave trough energy of the top boundary of a position in the target area purpose layer segment is less than the corresponding threshold value, the average wave peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold value, and the characteristic longitudinal wave impedance in the wave impedance inversion data body corresponding to the position is lower than the sandstone reservoir inversion longitudinal wave impedance threshold value, it is determined that the shale oil reservoir exists at the position, and the reservoir thickness of the position is calculated according to the number of data sampling points of the characteristic longitudinal wave impedance lower than the sandstone reservoir inversion longitudinal wave impedance threshold value in the wave impedance inversion data body corresponding to the position; otherwise, it is determined that the shale oil reservoir does not exist at the position, and the reservoir thickness of the position is marked as 0.

[0052] Because the sandstone and mudstone in the research area exist overlap, both are low P-wave impedance, so pure impedance cannot distinguish sandstone, but effective sandstone development area exists "head wave valley, foot wave peak" reflection characteristics, as shown in Figure 7 、 Figure 8 、 Figure 9 According to the above analysis results, the target area target interval (long 72 subinterval) interlayer type shale oil favorable reservoir of the embodiment meets the following three conditions:

[0053] (1) There is an inversion characteristic P-wave impedance lower than 10800 g / cm 3 *m / s in the wave impedance inversion data body;

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

[0055] (3) The average wave peak energy between the top boundary and the bottom boundary is higher than 100.

[0056] For convenience of representation, the average wave valley energy of the top boundary of each to-be-predicted position of the target area target interval is recorded as seismic attribute horizon data A, the average wave peak energy between the top boundary and the bottom boundary is recorded as seismic attribute horizon data B, and the wave impedance inversion data body obtained according to the characteristic P-wave impedance curve and the post-stack seismic data of the target area is recorded as seismic attribute horizon 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 satisfied, then the reservoir thickness H corresponding to the coordinate point is valued as 0.

[0058] If both of the two conditions that A is less than -100 and B is greater than 100 are satisfied, then the number of data sampling points in the inversion data body C that satisfy the characteristic P-wave impedance lower than 10800 g / cm 3 *m / s is counted and the reservoir thickness of the position is calculated to predict the thickness of the reservoir and to give the horizon data H under the coordinate point.

[0059] Wherein, the way to calculate the reservoir thickness of the position where the shale oil reservoir exists is as follows:

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

[0061] Wherein, H is the reservoir thickness, n is the number of data sampling points lower than the inversion P-wave impedance threshold value of the sandstone reservoir; T is the sampling rate; v is the reservoir velocity, that is, the propagation velocity of seismic waves in the reservoir, because the interlayer type shale oil reservoir is sandstone, the reservoir velocity of the sandstone in the research area where the target area is located is generally between 4000-4600 m / s, so the reservoir velocity here is taken as an empirical value of 4500 m / s.

[0062] The final shale oil reservoir thickness calculation result in the embodiment is shown in the figure Figure 6 The calculation result is greatly improved in accuracy compared with the conventional inversion method and is more in line with the geological law. Figures 10a-10c Three verification wells in the study area are studied, wherein Figure 10a The figure shows the comparison between the sandstone prediction result of well A in the well area and the actual mud logging result, Figure 10b The figure shows the comparison between the sandstone prediction result of well B in the well area and the actual mud logging result, Figure 10c The figure shows the comparison between the sandstone prediction result of well C in the well area and the actual mud logging result, wherein the gray part is the predicted high-quality reservoir development part, and the part between the dashed lines is the sandstone area, that is, the reservoir position, for example Figure 10a The predicted reservoir position is 608m-629.5m, and the actual well-acquired reservoir position is 607m-628m; Figure 10b 、 Figure 10c Similarly, it can be seen that the prediction accuracy is greatly improved compared with the conventional inversion method, the inversion result is basically consistent with the mud logging result, and the error is basically less than or equal to 2m, so the prediction result can provide a basis for horizontal well targeting.

[0063] The result of a new drilling well corresponding to a prediction is shown in the figure Figure 11 The gray part in the figure is the predicted high-quality reservoir development section; from the analysis of three oil and gas layer evaluation elements of oil layer classification, oiliness and porosity, the first-class reservoir, oil layer with oiliness greater than 45% and good oil layer with porosity greater than 8% in the new horizontal well are located in the predicted high-quality reservoir development section, the actual drilling result is consistent with the seismic inversion prediction, and it is proved that the application effect of the shale oil reservoir prediction method for the interbedded shale oil sweet spot in the embodiment is good. In summary, the shale oil reservoir prediction method in the embodiment uses the top boundary average wave trough energy and the interlayer average wave peak energy two seismic sensitive attributes according to the seismic reflection characteristics of the reservoir head wave trough and the foot wave peak, realizes inversion reservoir determination and attribute edge control, improves the shale oil reservoir prediction accuracy, and therefore can realize thin oil reservoir identification, improve the interbedded shale area sweet spot prediction level, and the method does not need to use a large amount of prestack seismic data and a large amount of well data, and is more suitable for reservoir sweet spot prediction in areas without prestack seismic data and sparse well pattern. In view of the problem that the sandstone and mudstone are difficult to distinguish in the interbedded shale oil reservoir prediction process, the curve reconstruction + waveform indication inversion is used, the seismic characteristics are maintained, and the thin reservoir identification ability is improved.

[0064] The application has the following characteristics:

[0065] 1) Using the seismic attribute characteristics of the "head wave trough, foot wave peak" of the reservoir development area, the average wave trough energy of the top boundary of the target area and the average wave peak energy between the top boundary and the bottom boundary are used for reservoir prediction, which can eliminate the influence of low impedance and remove shale, so as to calculate the thickness of the favorable reservoir of the interbedded shale.

[0066] 2) Since the longitudinal wave impedance in the target area is limited in identifying sand and shale, although the natural gamma ray is sensitive to identifying sand and shale, the post-stack seismic inversion can only obtain the longitudinal wave impedance data, and the seismic reflection characteristics only have a corresponding relationship with the seismic wave impedance interface; therefore, the characteristic curve reconstruction technology is used to reconstruct the inversion "characteristic curve" to obtain the characteristic longitudinal wave impedance curve of the target area which 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 construct the inversion model, so as to effectively improve the identification accuracy of the interbedded shale reservoir.

[0067] It should be understood that the above specific embodiments of the present application are only used for illustrative or explanatory purposes of the principles of the present application, and do not constitute a limitation on the present application.

Claims

1. A method of predicting a shale oil reservoir, characterized by, The method comprises the following steps: 1) calibrate the post-stack seismic data and the logging data of the target area to correspond the post-stack seismic data in time domain with the logging data in depth domain, wherein the target area comprises a sandstone facies section; 2) obtain the reflection characteristics of the top boundary and the bottom boundary of the reservoir in the target area according to the calibration result, and determine the threshold values corresponding to the average wave trough energy of the top boundary and the average wave peak energy between the top boundary and the bottom boundary of the target area respectively according to the reflection characteristics of the top boundary and the bottom boundary of the known reservoir in the target area; 3) obtain the average wave trough energy of the top boundary and the average wave peak energy between the top boundary and the bottom boundary of the target area at the to-be-predicted position of the target area according to the post-stack seismic data and the top boundary and bottom boundary stratum interpretation data of the target layer; obtain the characteristic P-wave impedance curve of the target area, and determine the sandstone reservoir inversion P-wave impedance threshold value according to the characteristic P-wave impedance curve; construct an inversion model according to the characteristic P-wave impedance curve of the target area and the post-stack seismic data to obtain the wave impedance inversion data volume; 4) identify the shale oil reservoir at the to-be-predicted position of the target area according to the wave impedance inversion data volume, the average wave trough energy of the top boundary and the average wave peak energy between the top boundary and the bottom boundary of the target area at the to-be-predicted position of the target area; if the average wave trough energy of the top boundary at a certain position is less than the corresponding threshold value, the average wave peak energy between the top boundary and the bottom boundary is greater than the corresponding threshold value, and the characteristic P-wave impedance in the wave impedance inversion data volume corresponding to the position is lower than the sandstone reservoir inversion P-wave impedance threshold value, it is determined that the shale oil reservoir exists at the position, and the reservoir thickness of the position is calculated according to the number of data sampling points in the wave impedance inversion data volume corresponding to the position, wherein the characteristic P-wave impedance is lower than the sandstone reservoir inversion P-wave impedance threshold value; otherwise, it is determined that the shale oil reservoir does not exist at the position, and the reservoir thickness of the position is marked as 0.

2. The method of predicting a shale oil reservoir according to claim 1, wherein, The reservoir thickness of the position where the shale oil reservoir exists is calculated in the following manner: H = n * T * v * 0.5 wherein H is the reservoir thickness, n is the number of data sampling points lower than the sandstone reservoir inversion P-wave impedance threshold value, T is the sampling rate, and v is the propagation velocity of seismic wave in the reservoir.

3. The method of predicting a shale oil reservoir according to claim 1 or 2, characterized by, The characteristic P-wave impedance curve of the target area is obtained in the following manner: extract the part of the P-wave impedance curve obtained according to the post-stack seismic data, wherein the frequency is less than or equal to the seismic effective frequency band, as the low-frequency part of the characteristic P-wave impedance curve, and extract the part of the natural gamma curve, wherein the frequency is greater than the seismic effective 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.

4. The method of claim 1 or 2, wherein, The sandstone reservoir inversion P-wave impedance threshold value is determined in the following manner: determine the inversion P-wave impedance ranges of the sandstone reservoir and the non-sandstone surrounding rock in the area where the target area is located through the wave impedance and natural gamma intersection analysis of the drilled wells in the target area, and determine the sandstone reservoir inversion P-wave impedance threshold value according to the inversion P-wave impedance ranges of the sandstone reservoir and the non-sandstone surrounding rock in the area where the target area is located.

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