Sand body depicting method based on seismic composite microphase under high-precision sequence framework

Abstract

The invention provides a sand body depicting method based on seismic composite microfacies under a high-precision sequence framework, which mainly comprises the following steps of: (1) analyzing geology-geophysical response characteristics of a sand body under a high-frequency sequence framework, namely (1.1) extracting and optimizing seismic attributes; (1.2) lithology distribution characteristic analysis; (1.3) analyzing and counting the relationship between the seismic attributes of the well point positions and rocks; (1.4) distribution characteristics of wave impedance; (1.5) lithology combination-sedimentary microfacies type-amplitude change one-dimensional forward modeling analysis is carried out; (1.6) carrying out two-dimensional forward modeling analysis based on sedimentary microfacies-cause sand body comparison; (2) depicting seismic attribute features and sand bodies, namely (2.1) extracting root mean square attributes and depicting the sand bodies; (2.2) performing planar distribution of characteristics on sand bodies of all the quasi-sequence groups; (3) earthquake-composite microfacies analysis: (3.1) earthquake composite microfacies type analysis; and (3.2) analyzing the composite microphase distribution characteristics in each period.

Description

Technical Field

[0001] The invention relates to the technical field of geological exploration, and in particular to a sand body characterization method based on seismic composite microfacies under a high-precision sequence framework. Background Art

[0002] Previous and previous work mainly focused on the study of regional sedimentary facies within the system domain framework, which has certain guiding significance for reservoir prediction, but cannot meet the needs of fine sand body carving and reservoir prediction. It is necessary to further use dense development well networks to carry out research on sedimentary microfacies under the high-frequency sequence framework and establish vertical sequences and planar distribution characteristic patterns of different sedimentary microfacies.

[0003] Shallow delta reservoirs have regularities to be found, and some regular clues have been found in exploration practice using seismic technology (amplitude attributes) (Lai Weicheng et al., 2009), but the geological meaning of seismic information lacks an interpretive basis:

[0004] ① The properties of the layers are extracted in equal parts, and the time is obvious. It emphasizes the analysis of the properties of the slices under the high-precision sequence framework. Therefore, high-precision sequence research is the basis;

[0005] ② The basis for seismic reservoir prediction is insufficient. How to strengthen the geological interpretation of seismic attributes is a powerful guarantee for seismic sedimentary microfacies analysis;

[0006] ③ The detailed characterization of sand bodies will play a significant role in providing an overview and also serve as the framework for the description of sedimentary microfacies and composite microfacies.

[0007] In the exploration of lithologic stratigraphic traps, people are in urgent need of the refinement of stratigraphic and sedimentary facies research. Sedimentary facies maps based on sedimentary subfacies in the system domain can no longer meet the needs of exploration, and there is an increasing call for sedimentary microfacies mapping. However, sedimentary microfacies in the traditional sense can only be depicted by dense development well networks of several hundred meters within a parasequence (small layer), which is impossible to achieve in the exploration stage. Sedimentary microfacies are generally not identifiable on seismic data, the main means in the exploration stage, so sedimentary microfacies research often does not play a practical guiding role in exploration. From the perspective of oil and gas exploration needs, there is an urgent need for a level between sedimentary subfacies and sedimentary microfacies.

[0008] The widely used seismic reservoir prediction technology provides a basis for filling this gap. Using seismic attributes, people can divide various seismic phase types (Lai Weicheng et al., 2006). They correspond to certain rock combinations and obviously represent a certain specific sedimentary phase unit. The smallest stratigraphic unit that can be distinguished by seismic reservoir prediction technology roughly corresponds to 1 / 2 wavelength or half of the phase axis, which is between the parasequence and the sequence group. From the perspective of the plane distribution range of this seismic phase, it is generally between the subphase and the microphase. Obviously, if this seismic phase unit can be given a definite sedimentological meaning and its relationship with the sedimentary subphase and sedimentary microphase can be straightened out, a sedimentary phase level can be added to the sedimentological theory. It has a clear sedimentological meaning and can fully meet the needs of oil and gas exploration. There is no rigorous theory for this level at present, so it can be called a seismic microphase for the time being. Summary of the invention

[0009] In view of the problems existing in the above-mentioned background technology, the present invention proposes a sand body characterization method based on seismic and composite microfacies under a high-precision sequence stratigraphic framework. The method has a reasonable concept and can make an interpretation of the sand bodies of seismic composite microfacies under a high-precision sequence stratigraphic framework that is more in line with sedimentological concepts, emphasize more on the genetic type of the sand bodies, and the interpretation results are more in line with geological laws and have more significance for genetic prediction.

[0010] In order to solve the above technical problems, the present invention provides a sand body characterization method based on seismic and composite microfacies under a high-precision sequence framework, which mainly includes the following steps:

[0011] (1) Analysis of sand body geological and geophysical response characteristics under high-frequency sequence framework

[0012] (1.1) Seismic attribute extraction and optimization;

[0013] (1.2) Analysis of lithology distribution characteristics;

[0014] (1.3) Analysis and statistics of the relationship between seismic attributes and lithology at well point locations;

[0015] (1.4) Distribution characteristics of wave impedance;

[0016] (1.5) One-dimensional forward analysis of lithology combination, sedimentary microfacies type and amplitude variation;

[0017] (1.6) Two-dimensional forward modeling based on the comparison of sedimentary microfacies and genetic sand bodies;

[0018] (2) Seismic attribute characteristics and sand body characterization

[0019] (2.1) RMS attribute extraction and sand body characterization;

[0020] (2.2) Characterization of the planar distribution characteristics of sand bodies in each parasequence group;

[0021] (3) Seismic composite microfacies analysis

[0022] (3.1) Analysis of seismic composite microfacies types;

[0023] (3.2) Analysis of the distribution characteristics of composite microfacies in different periods.

[0024] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein: the step (1.1) specifically extracts a number of attribute maps for each parasequence group in the key well area; through comprehensive analysis of seismic and drilling, accurate calibration of synthetic records is performed to estimate the sedimentary thickness of the target sand body on the seismic, and different time windows are selected to extract attributes.

[0025] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein the step (1.2) is based on drilling in the study area, statistically analyzing the relationship between lithology types, sandstone thickness, lithology combination types, and parasequence group development patterns and lithology combinations in different system domains, and directly applying the statistical results to the analysis of the mutual coupling relationship between the seismic attributes of the well point location-lithology combination relationship and the different lithology combinations-microfacies types-forward characteristics; specifically comprising the following steps:

[0026] (1.2.1) Analysis of lithology types and sandstone thickness distribution characteristics;

[0027] (1.2.2) Analysis of the main lithological combination characteristics under the sequence framework;

[0028] (1.2.3) Statistics of parasequence group types and their lithological combinations under the system tract framework.

[0029] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein the step (1.3) is to predict reservoir parameters based on the relationship between seismic attributes and reservoir parameters; specifically comprises the following steps:

[0030] (1.3.1) Statistical analysis of the relationship between the RMS amplitude between layers of parasequence groups and the lithology of well location;

[0031] (1.3.2)Statistics of the relationship between Strat imagic seismic facies and lithology.

[0032] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein the step (1.4) specifically includes the following steps:

[0033] (1.4.1) Analysis of factors affecting wave impedance

[0034] That is, through the geological information contained in velocity, density and wave impedance, the influence of depth factor, porosity factor and oil and gas content factor on wave impedance is analyzed;

[0035] (1.4.2) Analysis of distribution characteristics of wave impedance of different lithologies

[0036] The changing characteristics of wave impedance of oil and gas-bearing sandstone are analyzed in detail from three aspects: velocity, density and wave impedance.

[0037] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein: in the step (1.4.2), in order to significantly compare the relationship between mudstone, siltstone, fine sandstone, oil-bearing sandstone, gas-bearing sandstone and wave impedance in the study area, a lithology wave impedance probability distribution map is established.

[0038] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein the step (1.5) specifically includes the following steps:

[0039] (1.5.1) Simple single-layer sand body forward model analysis;

[0040] (1.5.2) Forward model analysis of a single distributary channel;

[0041] (1.5.3) Forward model analysis of multi-period diversion channels;

[0042] (1.5.4) Forward model analysis of lithology combination of sand-mud interbeds

[0043] (1.5.5) Forward model analysis of distant sand bars and sand beaches;

[0044] (1.5.6) Forward modeling analysis of composite microfacies of remote sand bar, estuary bar and distributary channel;

[0045] (1.5.7) Forward model analysis of composite microfacies of distributary channel system;

[0046] (1.5.8) Analysis of the relationship between oil and gas content and amplitude.

[0047] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein the step (1.6) specifically includes the following steps:

[0048] (1.6.1) 2D forward modeling analysis

[0049] Based on the establishment of earthquake model, forward simulation is realized through wave equation method;

[0050] (1.6.2) Analysis of spatial distribution patterns of typical sand bodies

[0051] That is, the vertical distribution pattern of the sand body is delineated by combining seismic and drilling data with plane and section amplitude characteristics;

[0052] (1.6.3) Analysis of seismic response patterns of typical sand bodies

[0053] By analyzing the sand body distribution characteristics of typical wells in this area, on the basis of statistical analysis of impedance and lithology combination of existing drilling wells, taking into account the sedimentary environment, lithology, superposition and pinch-out of sand bodies, a geological model consistent with the actual geological conditions is designed for the geological conditions of this area under different conditions. The wave equation method is used for simulation to obtain the geological-geophysical response model of typical sand bodies in key areas. The simulation results are compared with the actual results, and the corresponding parameters of the model are continuously modified to make the simulation results consistent with the actual seismic profiles, thereby obtaining the geophysical response models of various genetic sand bodies under different geological backgrounds.

[0054] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein: the seismic wave equation forward simulation algorithm in the step (1.6.1) includes:

[0055] ①High-order finite difference method

[0056] The simulation accuracy is improved by increasing the order of the difference equation. Using Taylor expansion, the function f(x) is expanded in the neighborhood of x0:

[0057]

[0058] Subtract the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f′(x):

[0059]

[0060] Add the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f″(x):

[0061]

[0062] ② Spectral method

[0063] The Fourier transform technology is used to solve the seismic wave field forward simulation of the wave equation, and the accuracy of the spatial derivative calculation is improved by the properties of the Fourier transform. Using the properties of the Fourier transform, the derivative of the function f(x) can be calculated by the following formula:

[0064]

[0065] Taking the acoustic wave equation as an example, the spatial derivative is calculated as follows:

[0066]

[0067] The time derivative is calculated using the leapfrog format:

[0068]

[0069] From this we can get the forward modeling equation:

[0070]

[0071] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein: the step (2.1) is to characterize the sand bodies of each parasequence group by extracting the interlayer root mean square amplitude of each parasequence group, strictly based on the geological interpretation of the attributes; and in the sand body interpretation, the sand bodies are qualitatively divided into thinner and thicker according to the relative strength of the amplitude.

[0072] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework, wherein: the step (2.2) is to characterize the planar distribution of sand bodies in different parasequence groups based on the analysis results in the step (1).

[0073] By adopting the above technical solution, the present invention has the following beneficial effects:

[0074] The sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention is reasonably conceived, and can explain the sand bodies of the seismic composite microfacies under these high-precision sequence frameworks in a more consistent with sedimentological concepts, emphasize more on the genetic type of the sand bodies, and the interpretation results are more in line with geological laws and have more significance for genetic prediction; at the same time, based on the establishment of a geological-seismic response relationship model under different sedimentary phase backgrounds, the sand body characterization method is simple and easy to use, simple and easy to implement, the prediction is consistent with the actual, and the consistency rate reaches more than 90%. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0076] Figure 1 This is a waveform classification diagram involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention (the waveform itself does not change much, but the waveform amplitude and wavelength change significantly;

[0077] Figure 2It is a schematic diagram of the pss1 waveform classification and lithology combination of the mL2 segment involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0078] Figure 3 It is a schematic diagram of the pss10 waveform classification and lithology combination of the mL2 segment involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0079] Figure 4 It is a schematic diagram of the influence of the oil-bearing layer on the velocity, density and wave impedance involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0080] Figure 5 It is a characteristic diagram of sandstone-mudstone wave impedance distribution involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0081] Figure 6 It is a characteristic diagram of velocity distribution of different lithologies involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0082] Figure 7 It is a wave impedance distribution characteristic diagram of the oil and gas content of sandstone involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0083] Figure 8 It is a simple single-layer sand body forward model diagram involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention;

[0084] Fig. 9 It is a schematic diagram of a staggered grid format of elastic wave simulation involved in the sand body characterization method based on seismic composite microfacies under a high-precision sequence framework of the present invention;

[0085] Fig.10 It is a schematic diagram of the plane distribution of the root mean square amplitude of different parasequence groups involved in the sand body characterization method based on the seismic composite microfacies under the high-precision sequence framework of the present invention. DETAILED DESCRIPTION

[0086] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] The present invention is further explained below in conjunction with specific implementation modes.

[0088] The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework provided in this embodiment includes the following steps:

[0089] (1) Analysis of sand body geological and geophysical response characteristics under high-frequency sequence framework

[0090] (1.1) Seismic attribute extraction and optimization

[0091] Amplitude statistics seismic attributes include root mean square amplitude, average absolute amplitude, maximum peak amplitude, average peak amplitude, maximum valley and peak value, absolute amplitude energy, total amplitude, average energy, total energy, average amplitude, average reflection intensity, average instantaneous frequency, average instantaneous phase, etc. These seismic attributes can reflect the lithology, stratigraphic sequence changes, unconformities, faults, fluid changes, reservoir porosity changes and other characteristics of the formation.

[0092] In the study, several attribute maps such as single layer interface, instantaneous phase between layers, root mean square amplitude and instantaneous frequency were extracted from the 11 parasequence groups divided in the Mingxia II section of the three key well areas.

[0093] Through the comprehensive analysis of seismic and drilling, and the precise calibration of synthetic records, the sedimentary thickness of the target sand body can be estimated on the seismic, and different time windows can be selected to extract attributes. According to the division results of the parasequence groups in this area, it generally corresponds to 1 / 4 to 2 / 3 wavelengths on the seismic, and the seismic time is roughly 15ms to 50ms. Considering that it is not easy to select the extraction time window due to the large time span, and considering the lithological combination and superposition style within each parasequence group, the attribute extraction between the upper and lower parasequence groups is finally adopted as the best.

[0094] Since various seismic attributes reflect different geological information, the average instantaneous frequency is used to detect amplitude absorption anomalies. Low values ​​often correspond to bright spots (high RMS amplitudes), indicating gas-bearing sandstones. The instantaneous phase can detect the distribution of oil and gas, and can also identify amplitude anomalies caused by tuning effects. It is a common attribute for predicting oil and gas content. The effective bandwidth is used to identify the changing area of ​​composite / single reflections. High values ​​of this attribute indicate relatively sharp reflection amplitudes and complex reflections, while low values ​​indicate isotropic reflections. It is a common attribute for predicting sandstone thickness.

[0095] At the same time, the phase in the attribute can well reflect the relationship between strata. This time, we also tried to extract this attribute, which is similar to the amplitude attribute in terms of plane distribution. The root mean square attribute is obtained by calculating the root mean square value of the amplitude of each sampling point in the seismic trace analysis window. Since the root mean square amplitude is squared before averaging, it is very sensitive to the change of amplitude, which is especially helpful in distinguishing abnormal bodies in seismic bodies. Therefore, in this chapter, the root mean square amplitude attribute will be used to analyze the distribution of sand bodies.

[0096] (1.2) Analysis of lithology distribution characteristics

[0097] The statistical analysis of lithologic distribution characteristics is based on drilling in the study area. The statistical contents include lithologic type, sandstone thickness, lithologic combination type, and the relationship between the development style of parasequence groups and lithologic combinations in different system domains. These statistical results will be directly applied to the analysis of the mutual coupling relationship between seismic attributes of well location - lithologic combination and different lithologic combinations - microfacies types - forward modeling characteristics.

[0098] (1.2.1) Analysis of lithology types and sandstone thickness distribution characteristics

[0099] Through the statistics of lithological data of each key block, it is known that the main lithologies of the target layer are sandstone, fine sandstone, unequal-grained sandstone, gravel-bearing sandstone, gravel-bearing fine sandstone, siltstone, muddy siltstone, silty mudstone, mudstone, etc.

[0100] The thickness of sand layers in each key block was statistically analyzed, and it was found that the maximum thickness of single sand bodies in the parasequence groups in BZ26, BZ29, and BZ34 were 20.5m, 25.5m, and 23m, respectively, and most of the thick sand bodies were concentrated in PSS1; the maximum sand body thickness in the middle and lower parts of the high-stand domain was mostly <10m, and the thinnest single sand bodies were all less than 1m. The frequency analysis of the distribution of sand body thickness in each parasequence group showed that single sand bodies were mostly distributed in thin layers of 1-3m, and most of them were siltstone; thick layers of sand greater than 10m mostly appeared in parasequence groups 1 and 11, corresponding to the bottom of the low-stand + water transgression domain and the top of the high-stand system domain, with coarse lithology.

[0101] (1.2.2) Analysis of main lithologic combination characteristics under sequence framework

[0102] From a macroscopic perspective, within the sequence framework of the three key areas, the lithologic combinations mainly include the following five types:

[0103] Mudstone intercalated with thin layers of sandstone: The upper and lower surrounding rocks are thick layers of mudstone (10-41m), with sandstone intercalated in the middle. The thickness of the sandstone is in the range of 1-3m, and its thickness is much smaller than that of the upper and lower surrounding rocks. This type of lithology combination is relatively common in the study area.

[0104] Mudstone intercalated with thick sandstone: large sections of gray or yellow sandstone greater than 8 m in thickness. The thickness of sandstone in some well locations can reach 27 m. The upper and lower surrounding rocks are mainly mudstone, and the thickness of the upper and lower mudstones is greater than or equivalent to that of sandstone.

[0105] Composite thick interbeds: Its characteristics are quite obvious, with several sections of sandstone separated by mudstone. The thickness of sandstone is 8-16m, and the thickness of mudstone is 0.8-13m. The response of sandstone on the logging curve is box-shaped.

[0106] Mudstone intercalated with medium-thick sandstone: the upper and lower surrounding rocks are thick mudstones, and the middle is sandstone. The thickness of the sandstone is 3-8m, and its thickness is less than that of the upper and lower surrounding rocks or the thickness is equal. The thickness of the mudstone is usually in the range of 6-23m, but the thickness of the mudstone in some wells can reach 40m. This type of lithology combination is also common in the study area.

[0107] Thin interbeds: It is characterized by frequent interbeds of thin sandstone and mudstone (mud: 1-3m; sand: 1-3m), with sandstone and mudstone appearing alternately, and sandstone appearing finger-like on the logging curve.

[0108] (1.2.3) Statistics of parasequence group types and lithological combinations under the system tract framework

[0109] Accretionary and progradational parasequence groups are developed in the high-stand system domain. Among them, the accretionary parasequence groups have three types of lithological combinations, namely, large sets of mudstones interbedded with thin sandstones, large sets of mudstones interbedded with medium-layer sandstones, and sand-mud interbeds. The progradational parasequence groups in the high-stand domain have two types of lithological combinations: sand-mud abrupt contact type and sand-mud gradual contact type.

[0110] The lake expansion area can be divided into early and late lake expansion areas. In the early lake expansion area, retrogradational and progradational parasequence groups are developed. The retrogradational parasequence group is most typical in the study area, with PSS1. Two types of lithological combinations are developed, namely, sand-mud gradual change type and large set of sandstone and mudstone type. The progradational parasequence group develops sand-mud gradual change contact type and sand-mud abrupt change contact-large set of sand and mudstone contact type.

[0111] In the late stage of lake expansion, the main type of parasequence formation is aggradational-retrogradational parasequence formation, in which two types of lithological combinations are developed: large sets of mudstone interbedded with middle-layer sandstone and interbedded sandstone and mudstone (mudstone is thicker than sandstone). In the retrogradational parasequence formation, there are sand-mud gradual contact type lithological combinations and sand-mud abrupt contact type lithological combinations.

[0112] (1.3) Analysis and statistics of the relationship between seismic attributes and lithology at well location

[0113] According to the relationship between seismic attributes and reservoir parameters, reservoir parameters can be predicted. The previous lithology statistical analysis shows that due to the significantly low sand-to-ground ratio in the study area, it is very advantageous and feasible to carry out statistical analysis of the strength of lithology combination and seismic amplitude at the well point location. At the same time, in the process of research, Stratification imaginary seismic phase analysis was carried out on three key areas based on the high-precision sequence division results and the corresponding seismic phase maps were extracted. Combined with the relationship between drilling lithology combination analysis and seismic phase, the main purpose is to compare with the root mean square amplitude.

[0114] (1.3.1) Statistical analysis of the relationship between the RMS amplitude of parasequence layers and the lithology of well location

[0115] Due to the characteristics of the lithology distribution in this area, the amplitude distribution on the plane should be able to directly reflect the planar development of the sand body. The stronger the amplitude, the thicker the sand body, the weaker the amplitude, the less developed the sand body. The medium-strong amplitude generally indicates a large set of mudstones with thin layers of sand bodies. However, the overall paleogeology and sedimentary background must be considered at the same time. This statistical method was used in the study to conduct detailed statistics on different parasequence groups in three key areas, and the following main conclusions were obtained:

[0116] ① The lithologic combination of the composite thick interbeds corresponds to the strong amplitude;

[0117] ② The lithology combination of mudstone and thick sandstone corresponds to medium-strong amplitude;

[0118] ③ The lithology combination of mudstone and medium-thick sandstone corresponds to medium amplitude;

[0119] ④ The lithologic combination of thin interbedded mud and sand corresponds to medium-weak amplitude;

[0120] ⑤ The lithology combination dominated by large sets of mudstone intercalated with thin layers of sandstone or large sets of mudstone corresponds to weak amplitude.

[0121] Statistical analysis shows that there is a good correspondence between amplitude and lithology combination. The consistency rate between all logging lithology combinations and amplitude attributes in the three key zones is over 90%, which provides favorable evidence for our later use of strong and medium-strong amplitude to predict sandstone.

[0122] (1.3.2) Statistics of the relationship between Stratification imaginary seismic facies and lithology

[0123] In order to better reflect the macroscopic distribution of the anomaly on the plane and the comparative and unified analysis of the amplitude, the equal-thickness intervals of each parasequence group were established, and the waveforms were further classified into 12 categories within the intervals ( Figure 1 ).

[0124] Since the waveform contains a lot of seismic information, and the stratigraphic interpretation scheme, the time window of the waveform segment, and the number of waveforms all have a certain impact on its planar characteristics, in order to better compare with the amplitude, this time when conducting waveform seismic phase sand body prediction analysis, the analysis will be conducted from the perspective of the waveform itself (peaks, troughs) and the size of the waveform amplitude.

[0125] In this study, waveform seismic phases of 11 parasequence groups in the mL2 interval of BZ26, BZ29, and BZ34 were analyzed in non-isochronous intervals. The relationship between waveform characteristics and lithologic combinations was analyzed in particular in the BZ34 area. Since the parasequence groups pss1 and pss10 are located in the transgressive and highstand system domains, respectively, their lithologic characteristics are significantly different, and the relationship between waveforms and lithologic combinations is also different, so these two parasequence groups were analyzed in detail.

[0126] PSS1 sandstone is relatively developed, with medium-high frequency as the main feature. When thin layers of sandstone are developed in a large set of mudstone, a relatively low-frequency waveform feature can be formed. According to the lithology combination and waveform features, it can be divided into three categories (see Figure 2 ).

[0127] Relatively high frequency: reflects the lithological combination dominated by medium-thick sandstone in the large set of mudstone;

[0128] Relative medium frequency: reflects the lithological combination dominated by mudstone and thickened sandstone;

[0129] Relatively low frequency: reflects the lithological combination characteristics of large sets of mudstone and thin layers of sand.

[0130] The mudstone in PSS10 is relatively well developed and can be divided into three categories according to the relationship between the distribution of the seismic phase plane of PSS10 and the type of drilling combination (see Figure 3 The relatively high-frequency waveform reflects the lithological combination of a large set of mudstones with intercalated thin layers of sandstone; the relatively medium-frequency waveform reflects the lithological combination of mudstones and thick layers of sandstone; the relatively low-frequency waveform reflects the lithological combination of a large set of mudstones with intercalated medium-thick layers of sandstone and intercalated medium-thick layers of sand and mud.

[0131] The 12 types of theoretical waveforms of STRAT I MAG IC seismic phases were analyzed based on waveform characteristics and waveform amplitude changes. After color adjustment, the waveform seismic phase plane diagrams of all parasequence groups were compared with the root mean square amplitude diagrams, and it was found that the two had a certain matching relationship, but the overall trend did not correspond well.

[0132] According to the planar distribution analysis of waveform seismic phases, it is found that the target layer sand land in this area is relatively low, the shallow water delta system is dominated by distributary channels, and the shallow water delta system deposition is relatively complex during the lake level fluctuation cycle, resulting in the diversity of sand body distribution. Therefore, the correspondence between the waveform and frequency changes and the lithology combination in this area is not ideal, and the lithology prediction using seismic phases will have multiple solutions. On the contrary, the strong and weak changes in amplitude have a good correspondence with lithology in this area, so the reliability of sand body prediction by RMS amplitude is further demonstrated through seismic phase analysis.

[0133] (1.4) Analysis of the distribution characteristics of wave impedance

[0134] Wave impedance is the product of rock density and longitudinal wave velocity, which means that wave impedance is a rock property, rather than representing interface characteristics like seismic reflection data. Wave impedance itself is a physical parameter of rock (the product of wave velocity and density), and has a strong ability to describe rock properties (such as lithology, rock porosity and hydrocarbon saturation, etc.).

[0135] (1.4.1) Analysis of factors affecting wave impedance

[0136] Seismic method is the main means in current petroleum geophysical exploration. Changes in lithology, rock porosity and the content of fluid (such as oil and gas) in the pores will affect the velocity of seismic waves. On the other hand, the seismic parameters of rocks are also affected by changes in pressure and temperature in the formation. The depth of the rock formation and the frequency of exploration will affect the seismic characteristics of the rock. In fact, the elastic wave velocity is the result of the combined effect of the above factors.

[0137] Through the geological information contained in velocity, density and wave impedance, the influence of some factors on wave impedance is briefly analyzed.

[0138] ① Depth

[0139] Generally, under the same conditions of lithology and geological age, the velocity of seismic waves increases with the increase of rock burial depth. When the rock burial depth increases, the combined effect of static geopressure and pressure in the rock formation usually leads to an increase in elastic wave velocity. However, the change in velocity gradient decreases with the increase of burial depth.

[0140] As the depth increases, the porosity of sedimentary rocks decreases, while the density increases. This is the result of metamorphism and epigenesis under the action of static pressure that increases with depth. As the depth increases, the increase in temperature accelerates the densification of rocks. Wave impedance is the product of rock density and longitudinal wave velocity, and it also gradually increases with depth.

[0141] Because the thickness of the target layer in this study is relatively small, the changes in velocity, density, and wave impedance with depth can be ignored, so the influence of depth on the three is not considered.

[0142] ②Porosity

[0143] Porosity is one of the factors that affect wave impedance. Generally speaking, when other factors are the same, high-porosity rocks generally have low velocities, while low-porosity rocks show high velocities. The presence of cracks can also cause the wave velocity of rock samples to be low. Sometimes the impact of cracks is more obvious than that of pores, especially cracks that are not completely filled. Whether it is clastic rock or carbonate rock, the increase in mud content in the pores will lead to a decrease in wave propagation velocity. For example, when the mud content of carbonate rock increases from 5% to 15%, the velocity can be reduced by 17% to 20%. For sandstone, low velocity can reflect both an increase in porosity and an increase in mud content. Therefore, mud correction should be made when obtaining porosity for formations with a large mud content, and the effect of mud content on impedance is more complicated.

[0144] Based on the actual situation in this area, the influence of lithology on wave impedance is far greater than that of porosity, so the influence of porosity can be ignored.

[0145] ③ Oil and gas content

[0146] The effect of rock saturation on wave velocity is a very concerned issue in oil exploration. The effect of sandstone on seismic wave velocity is also very obvious when it is saturated with gas, oil, and water. Scholars have used the collected data to give a rough diagram of the effect of sandstone saturated with oil, gas, and water on seismic wave velocity. They pointed out that in shallow rock formations, a small amount of gas will significantly reduce the rock velocity, but when the gas content in the formation reaches 5%, increasing the gas saturation will only have a small effect on the velocity of the rock formation, which will cause the prospective gas reservoir and micro-gas-bearing layer to be similar in seismic velocity. The relationship between water-saturated sandstone, gas-saturated sandstone, and oil-saturated sandstone is: the velocity difference between oil and water-saturated sandstone is very small; the velocity difference between gas-saturated and water- and oil-saturated sandstone is large when the depth is less than 1600m, and when the depth is greater than 1600m, the difference is relatively small; the velocity difference between gas-saturated sandstone and shale is large within a small depth range, but the difference is small when it is greater than about 2000m. The acoustic impedance of gas-bearing sandstone is lower than that of oil-bearing and water-bearing sandstone. For the same rock sample, the longitudinal wave velocity is higher when it is saturated with oil than when it is saturated with water, and higher when it is saturated with water than when it is dry. However, as the pressure increases, the longitudinal wave velocity of both oil-saturated and water-saturated rock samples will increase, but the increase in the velocity when saturated with water is greater than the increase in the velocity when saturated with oil, and the longitudinal wave velocities of the two are getting closer and closer.

[0147] Well BZ25-1-9 contains no oil sandstone at 1846-1848m, and oil sandstone at 1850.4-1856.4m. Figure 4 -a, 4-b, 4-c show that the velocity of the oil-bearing sandstone is about 2600-2900 m / s and the density is 2.1-2.2 g / cm 3 , impedance value is about 5600-6100m / s*g / cm 3 , while the velocity of oil-free sandstone is about 2700-3000m / s, and the impedance value is about 6000-6500m / s*g / cm 3 The impedance of the oil-bearing layer is lower than that of normal sandstone, the density is reduced, and the impedance is smaller.

[0148] (1.4.2) Analysis of distribution characteristics of wave impedance of different lithologies

[0149] The purpose of analyzing the impact of drilling lithology conditions is to have a clear understanding of logging data. However, external factors only play a role of interference, and the decisive factor is the composition and structure of the rock itself. Generally, sandstone has the largest wave impedance, followed by mud sandstone, and mudstone has the smallest wave impedance. This understanding lays the foundation for inversion and lithology interpretation, but contradictions are often encountered in the prediction of river facies reservoirs. For example, after analyzing and statistically analyzing the logging data in the study area, Figure 5 The fitted intersection diagram of wave impedance and natural potential and Figure 6The probability distribution diagram of the wave impedance range shows that the wave impedance range of mudstone, siltstone and fine sandstone in the study area is obviously distributed.

[0150] There are bound to be differences in logging data from different blocks in the study area. Due to the influence of various environmental factors such as temperature and climate, the diagenetic environment and lithological characteristics of different well locations are bound to be different. Therefore, the wave impedance values ​​of some logging mudstones, siltstones and fine sandstones are not significantly different. However, what is very helpful for our research is that when sandstone contains oil or gas, the wave impedance value range will become significantly smaller, and it will be clearly distinguished from the wave impedance of sandstone and mudstone. The following is a detailed analysis of the changing characteristics of the wave impedance of oil and gas sandstone from three aspects: velocity, density and wave impedance.

[0151] According to the statistics of many wells, the formation velocity distribution of different lithologies in this area is as follows: sandstone velocity is 2800-3200m / s, mudstone velocity is 2700-3000m / s, oil-bearing sandstone velocity is 2600-2800m / s, gas-bearing sandstone velocity is 2100-2400m / s. In general, sandstone has a higher velocity than mudstone, and we can accurately separate them.

[0152] However, as the depth increases, the density of clastic rocks increases the most, with mudstone being the most dense, followed by sandy mudstone, and the rigid sandstone being slightly smaller. The density increase with depth is not so obvious for carbonate rocks, metamorphic rocks, and igneous rocks. The density of carbonate rocks increases, and the structure of the pore space and the degree of fissures play a big role. Therefore, the geological information of some rock formations can be obtained from density data. The density of siltstone is relatively large, ranging from 2.2-2.4g / cm 3 The second is mudstone, about 2.1-2.3g / cm 3 The density of gas-bearing sandstone is relatively low, mostly concentrated in the range of 1.9-2.1 g / cm 3 .

[0153] Wave impedance combines information on velocity and density, and studying the changes in wave impedance can better reflect the geological information of rock formations. According to statistics, the wave impedance of the target layer sandstone is 6500-8000, the wave impedance of mudstone is 5500-7000, the wave impedance of oil-bearing sandstone is 5500-6500, and the wave impedance of gas-bearing sandstone is 4500-5500. From a statistical point of view, the wave impedance of gas-bearing sandstone and gas-bearing sandstone in the study area is significantly lower, which is significantly different from the wave impedance of mudstone and oil-free sandstone.

[0154] In order to significantly compare the relationship between mudstone, siltstone, fine sandstone, oil-bearing sandstone, gas-bearing sandstone and wave impedance in the study area, a lithology wave impedance probability distribution diagram was established, such as Figure 7In this study area, shallow water deltas are mainly developed, and the lithology is mostly thin interbedded sandstone and mudstone. The thickness of sandstone is relatively thin, and the difference in wave impedance between sandstone and mudstone is not obvious. However, the wave impedance of oil and gas-bearing sandstone changes significantly, and the value range becomes smaller, which enhances the difference and provides favorable conditions for better distinguishing oil and gas content.

[0155] The lithology statistics show that the lithology of this area is relatively simple, with sandstone and mudstone as the development types. The wave impedance statistical analysis found that the impedance of mudstone is significantly lower than that of sandstone. The wave impedance of sandstone and mudstone can be separated and the difference is large, which provides a theoretical basis for forward modeling and using amplitude to predict sand bodies in this area according to lithology-sedimentary microfacies types.

[0156] (1.5) One-dimensional forward modeling analysis of lithology combination, sedimentary microfacies type and amplitude variation

[0157] (1.5.1) Simple single-layer sand body forward model analysis

[0158] Statistical analysis of drilling shows that the sand layers in this area are composite sand bodies. The maximum sandstone thickness is 16m and the minimum is 0.5m. More than 90% of the sandstone thickness is less than 10m. Due to the limitation of seismic resolution, it is impossible to distinguish a single thin layer. In other words, an event axis on a conventional seismic profile is caused by the superposition of reflections from several thin layers.

[0159] According to rock physics analysis, the reservoir velocity is mainly concentrated in 2900-3150m / s, and its 1 / 4 wavelength is about 24 meters. Considering the tuning effect, the total thickness of the sand body is 24m when designing the forward model. Considering that the main frequency of the sub-wave in this area is 30Hz, 1 / 4 is about 24m, so a simple model is designed:

[0160] The total thickness of the formation is 48m, and the thicknesses of the single-layer sand bodies are 24m, 20m, 16m, 12m, 8m, 4m, and 2m respectively. The velocity of the sandstone is 3100m / s, and the velocity of the mudstone is 2900m / s. The density is calculated according to the Gadner empirical formula. The sub-wave frequency is 30Hz. The simulation results are shown in Figure 8 In the model, red represents mudstone and yellow represents sandstone.

[0161] From the forward model, we can see that as the thickness of the single-layer sand body decreases, the amplitude continues to weaken, and the reflection interface moves downward. When the formation contains 2m of sandstone, the amplitude is the weakest. When the thickness is less than the tuning thickness, the formation thickness can only be determined by studying the amplitude. Therefore, the amplitude is closely related to the thickness of the sandstone and mudstone.

[0162] (1.5.2) Forward model analysis of a single diversion channel

[0163] The model is mainly derived from the lithological combination of the parasequence group in the early stage of lake expansion and the late stage of high-stand, which is a single thick sandstone (sandstone>10m; mudstone>20m). The single well sedimentary microfacies analysis is mostly thick distributary channels. The forward model results show that the seismic reflection of this type of sedimentary microfacies sandstone is mainly strong amplitude.

[0164] (1.5.3) Multi-period diversion channel forward model

[0165] According to the characteristics of sandstone development in the early stage of lake expansion and the late stage of high-stand, there are obvious superposition of multiple thick layers (sandstone>10m), and the mudstone between sandstone is thin, often less than 10m. The forward model results show that this set of lithology combinations are mostly composite strong amplitudes, and the drilling microfacies analysis belongs to a multi-stage distributary channel combination, which is mainly developed in the front of the shallow water delta, and is manifested as the superposition of multiple thick distributary channel sand bodies.

[0166] (1.5.4) Forward model analysis of lithology combination of sand-mud interbeds

[0167] From the perspective of lithologic combination, it can be divided into mudstone with thin sand and mudstone with medium sand. In general, mudstone is thicker than sandstone, with sandstone being 2-6m and mudstone being 3-12m. It mainly developed in the early stage of high stand, followed by the late stage of lake expansion. The forward simulation results show that the amplitude and wave group characteristics of this lithologic combination are composite medium-weak amplitude, among which the amplitude of mudstone with medium sandstone is significantly higher than that of thin sand. The drilling sedimentary microfacies analysis believes that this set of lithologic combination is a thin underwater distributary channel and far sand bar.

[0168] (1.5.5) Forward model analysis of distant sand bars and sand beaches

[0169] This type is a large set of mudstone with medium-thin sandstone, of which sandstone is 1-8m and mudstone is 12-40m. It mainly develops in the early stage of high stand, and is also distributed in the late stage of lake expansion. The amplitude characteristics are composite medium-weak amplitude, with weak amplitude being the most typical. It often reflects the sedimentary microfacies of the far sand bar or shallow lake sand beach at the delta front.

[0170] (1.5.6) Forward model analysis of composite microfacies of remote sand bar, estuary bar and diversion channel

[0171] The lithology is a progradational superposition, with sandstone 2-16m and mudstone 3-40m. The top sandstone is generally thicker, about 8-10m. It mainly developed in the late high stand, and the late progradational parasequence group can also be seen in the lake expansion area. The forward modeling result is a composite wave with a medium-strong amplitude.

[0172] (1.5.7) Forward model analysis of composite microfacies of distributary channel system

[0173] The lithology combination is a retrograde lithology combination, with sandstone 2-14m and mudstone 3-40m. The grain size of the sandstone varies greatly. The bottom sandstone of the combination near the edge of the basin, such as the BZ29 and BZ26 well areas, is thicker and coarser, mainly reflecting the composite sedimentary microfacies combination of the inner front (distributary channel-breach fan); in the center of the basin, such as the BZ34 well area, this type of lithology combination reflects the positive cycle sequence in which the lithology gradually thins as the base level gradually rises, and is mostly a composite microfacies of the distributary channel system composed of multiple distributary channels (possibly including breach fans). The forward modeling results show that this set of strata has two phase axes, of which the upper amplitude is medium-weak and the lower reflection amplitude is strong.

[0174] (1.5.8) Analysis of the relationship between oil and gas content and amplitude

[0175] The previous statistical analysis shows that the general rule between attributes and lithology is: strong amplitude corresponds to lithology combinations with relatively large differences in upper and lower lithology, reflecting the large difference in lithology wave impedance within the parasequence group; when the sandstone contains oil and gas, the wave impedance of the oil and gas sandstone decreases, generally lower than the wave impedance of mudstone. The impact on the seismic wave reflection amplitude is mainly reflected in the magnitude of the upper and lower impedance differences of the oil and gas sandstone. The greater the difference in impedance between the oil and gas sandstone and the pure sandstone or mudstone, the stronger the amplitude, and vice versa. However, the specific impact of oil and gas on the amplitude needs to be analyzed through one-dimensional forward modeling.

[0176] The BZ34-1-3 well pss7 consists of a set of oil-bearing sandstones at the bottom, a set of poor oil-bearing sandstones in the middle, and a layer of gas-bearing sandstones at the top. According to its forward seismic response, when the sandstone contains oil and gas, the amplitude is significantly enhanced. When the influence of oil and gas is removed, the amplitude is significantly weakened. In order to verify the influence of sandstone oil and gas content on the amplitude, the influence of oil and gas content on the amplitude is analyzed according to its seismic response.

[0177] The model is established based on the pss7 of the BZ34-1-3 well. The forward modeling results show that the oil or gas content in the sandstone has a significant impact on the amplitude, which increases the amplitude and changes the polarity of the seismic reflection wave. Gas-bearing sandstone of the same thickness has a greater impact on the amplitude than oil-bearing sandstone. The amplitude of thin gas-bearing sandstone is enhanced and the interface is lifted. It can be seen that when oil and gas appear at the same time, the amplitude is weakened compared with the single oil-bearing or gas-bearing model. It can be seen that when the formation thickness is less than the coordination thickness, the seismic reflection wave is the superposition of multiple seismic reflections less than the coordination thickness. This superposition may be the superposition of multiple strong amplitudes to enhance the amplitude, or it may be the cancellation of multiple amplitudes to weaken the amplitude.

[0178] Amplitude is the difference in wave impedance of the reflection interface. There are many factors that affect the change of amplitude, and lithology is only one of them. Combined with the oil and gas content of the target layer in the study area, the influence of lithology combination and oil and gas content on the amplitude is analyzed. Different lithology combinations will produce different amplitudes. Oil and gas in sandstone can indeed enhance the amplitude, but when multiple layers of oil and gas layers appear, the amplitude is not the strongest. Through analysis, it is found that the thickness of the formation, lithology combination, sandstone thickness, and oil and gas content all have an impact on the amplitude. To distinguish the amplitude differences caused by lithology and analyze what exactly causes the amplitude anomaly in this area, one-dimensional forward modeling is far from enough and requires multi-faceted analysis.

[0179] (1.6) Two-dimensional forward modeling based on sedimentary microfacies-genetic sand body comparison

[0180] (1.6.1) 2D forward modeling analysis

[0181] Due to the uncertainty of the seismic inversion process, the conclusion of seismic data interpretation is often not unique. Therefore, it is necessary to establish a geological model and make corresponding theoretical seismic traces (forward simulation) based on known logging data or geological data, assuming the thickness, density and velocity of the formation according to the possible stratum lithology combination. This theoretical seismic trace is compared with the actual seismic time section trace, and the assumed values ​​of the model parameters such as stratum thickness, density and velocity are continuously adjusted, and repeated iterations are performed until the theoretical trace and the actual trace are optimally fitted.

[0182] There are two main types of forward modeling methods, namely the ray method in geometric seismology and the wave equation method in physical seismology. The ray tracing method uses seismic wavelets and the reflection coefficient of the interface or geological body to perform deconvolution operations when synthesizing records. Its biggest feature is that it explains the kinematic characteristics of seismic wave propagation. In physical seismology, the seismic records synthesized by the wave equation method simulate the seismic wave field by solving the numerical solution of the wave equation. In the seismic records synthesized by the wave equation, in addition to maintaining the kinematic characteristics of seismic wave propagation, the dynamic characteristics of seismic wave propagation are also explained. Most of the previous forward modeling methods used simple convolution forward modeling methods to simulate the synthetic records of the target layer, which had poor similarity with the actual situation. The accurate method should be to use wave theory to simulate the shot gather records according to the actual field observation system, and perform velocity analysis, horizontal superposition, and offset on the shot gather records to obtain synthetic records, and then repeatedly compare and correct with the actual data, thereby greatly improving the accuracy of the interpretation results.

[0183] Two-dimensional forward modeling is based on one-dimensional forward modeling. According to actual geological data and geological knowledge, a geological model is established, the seismic response is obtained based on the model, the seismic response is compared with the actual seismic profile, and the geological model is continuously adjusted to achieve the greatest similarity between the geological model and the seismic profile.

[0184] This study uses the wave equation method to achieve forward simulation based on the establishment of an earthquake model. The seismic wave equation forward simulation algorithm is as follows:

[0185] ①High-order finite difference method

[0186] The accuracy of the simulation is improved by increasing the order of the difference equation. Using Taylor expansion, the function f(x) is expanded in the neighborhood of x0:

[0187]

[0188]

[0189] Subtract the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f′(x):

[0190]

[0191] Add the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f″(x):

[0192]

[0193] The same method can be used to construct difference equations with better than second-order accuracy, but the calculation of the derivatives will use more grid points, which will increase the computational cost.

[0194] The form of the differential grid will affect the accuracy of the wave field simulation. In the differential simulation algorithm used in the past, the wave field points and medium parameters were defined on rectangular integer grid points, and the simulation accuracy was lower than the current advanced staggered grid differential technology. The staggered grid technology defines variables at the halfway point between the grid points, and the wave field and medium parameters occupy different points, thus forming a "staggered" grid. Fig. 9 An example of staggered difference grid for differencing of elastic wave equation is given, where stress components and displacement velocity components occupy different half-range grid points.

[0195] ② Spectral method

[0196] The spectral method is a method of seismic wave field forward modeling that uses Fourier transform technology to solve the wave equation. It improves the accuracy of spatial derivative calculations through the properties of Fourier transform. Using the properties of Fourier transform, the derivative of the function f(x) can be calculated using the following formula:

[0197]

[0198] Taking the acoustic wave equation as an example, the spatial derivative is calculated as follows:

[0199]

[0200] The time derivative is calculated using the leapfrog format:

[0201]

[0202] From this we can get the forward modeling equation:

[0203]

[0204] The same method can also be used to obtain the forward simulation algorithm of the elastic medium wave equation.

[0205] The specific seismic model establishment method for this study is as follows: First, a geological model is established based on geological knowledge and drilling and logging data. The velocity of sandstone and mudstone is statistically calculated from the well data. The velocity of sandstone is 2900-3150m / s, and the velocity of mudstone is 2700-2900m / s. The sub-wave frequency is extracted, and the main frequency is about 30Hz. The seismic wave field is forward modeled to obtain the seismic response of the model, and the seismic response is compared with the actual seismic profile. The geological model is continuously adjusted to achieve the maximum similarity between the geological model and the seismic profile. The advantage of this method is that the wave theory is used to simulate the shot collection records according to the actual field observation system, and the shot collection records are subjected to velocity analysis, horizontal superposition, and offset to obtain synthetic records, which are then repeatedly compared and corrected with the actual data to improve the accuracy of the interpretation results.

[0206] After identifying the seismic phase and interpreting its sedimentary phase, the type of reservoir and its position on the profile can be roughly determined. However, due to the non-uniqueness of the seismic phase interpretation results, especially in areas with few wells, the superposition relationship of sand bodies, pinch-out mode, etc., it is necessary to use model forward modeling technology to further verify the interpretation results.

[0207] (1.6.2) Analysis of spatial distribution patterns of typical sand bodies

[0208] Combining seismic and drilling data as well as plane and profile amplitude characteristics, the vertical distribution pattern of sand bodies is outlined. The sand bodies are mostly not connected in the vertical distribution, but there is a certain regularity in the vertical development. Generally, sand bodies are more developed along the sequence interface and parasequence group interface. In the early stage of lake expansion (PSS1), the delta plain subfacies distributary channel and inter-distributary channel microfacies are developed. The sand bodies are thick and relatively coarse in grain size, and they are in lateral superposition and splicing contact with each other. Seismically, it is characterized by medium-strong amplitude and worm-like to wavy reflection characteristics. In the middle stage of lake expansion, the delta plain subfacies distributary channel and inter-distributary channel microfacies are developed, but the sand bodies are isolated plate-like contact types, which are characterized by medium-low continuity and medium-strong amplitude wavy reflection characteristics in seismic. In the late stage of lake expansion and early stage of high-stand, the delta plain subfacies is developed, and the sand bodies are mostly far-sand bars, sand beaches and other microfacies. Isolated lens-shaped sand bodies are often seen, which are characterized by low continuity, medium-weak amplitude, worm-like to mound-like seismic reflection characteristics in seismic. In the middle of the high-stand, the delta front subfacies developed, mainly distributary channels. In seismic, it is characterized by medium-low continuity, medium-weak amplitude, and wavy to lenticular reflection characteristics. In the upper part of the high-stand, the delta front distributary channel sheet sand microfacies developed, and many amalgamated plate-like sand bodies were developed, which were characterized by high continuity and strong amplitude wavy reflection characteristics in seismic.

[0209] (1.6.3) Analysis of seismic response patterns of typical sand bodies

[0210] By analyzing the sand body distribution characteristics of typical wells in this area, on the basis of statistical analysis of impedance and lithology combination of existing wells, taking into account the sedimentary environment, lithology, superposition and pinch-out of sand bodies, a geological model consistent with the actual geological conditions is designed for the geological conditions of this area under the control of different sedimentary environments, lithology, oil and gas content and other conditions. The wave equation method is used for simulation to obtain the geological-geophysical response model of typical sand bodies in key areas. The simulation results are compared with the actual results, and the corresponding parameters of the model are continuously modified to make the simulation results consistent with the actual seismic profiles, thereby obtaining the geophysical response models of various genetic sand bodies under different geological backgrounds.

[0211] During the specific research process, the influence of oil and gas content and the superposition relationship of sand bodies on the seismic profile was fully considered. By repeatedly adjusting the geological model, the seismic response was made to achieve maximum similarity with the geological model, laying a solid foundation for seismic interpretation and reservoir prediction.

[0212] The geological model was designed based on the established sand body geological conceptual model, and the corresponding seismic records were obtained through forward simulation. The seismic forward response showed that the seismic reflection characteristics had a good correspondence with the actual geological model.

[0213] Taking the BZ34 area as an example, an ideal model for sand body comparison in the BZ34 area was established by combining well-seismic analysis with sand body comparison based on the well-linked section of wells BZ34-3-1—BZ34-3-2D—BZ34-1 S-2—BZ34-1 S-1—BZ34-1-5—BZ34-1-6.

[0214] From the comparison of sand bodies in the early stage of lake expansion (PSS1+PSS2) and their forward modeling results, it can be concluded that the early sand bodies have good lateral connectivity and are in lateral splicing contact. The seismic reflection continuity of the two-dimensional forward modeling results is poor but the amplitude is strong, reflecting the mutual superposition and destruction of multi-stage distributary channels. The actual seismic profile has strong stratum fragmentation due to the later faulting, but its macroscopic reflection characteristics are consistent with the forward modeling results after the layer is flattened.

[0215] The middle part of the sequence includes late lake expansion and early high stand sediments (PSS3-PSS6), with isolated sand bodies and well-developed mudstone. After the actual seismic profile was flattened, it was found that the lateral continuity was extremely poor. In the sand body development area, a "bright spot" reflection configuration with medium-strong amplitude was visible. The forward modeling results were more obvious, with obvious isolated lens-shaped reflection features. However, due to the changes in sand body velocity, thickness, lateral extension distance, etc., the amplitude of different sand bodies varies greatly.

[0216] The upper part of the sequence is a high-stand late deposit (PSS7-PSS11), the thickness of the sand body gradually increases, the lateral connectivity changes, and it is in plate-like contact. In the actual seismic profile, a set of parallel-subparallel-wavy reflection waves with good lateral continuity, strong amplitude, and good lateral continuity are developed near the interface of the parasequence group PSSB9 and PSSB10. The two-dimensional forward modeling shows the same characteristics, and the phenomenon of poor continuity and weakened amplitude at the right end of the profile is also very consistent with the actual profile.

[0217] (2) Seismic attribute characteristics and sand body characterization

[0218] (2.1) RMS attribute extraction and sand body characterization

[0219] Based on the detailed analysis of the geological and geophysical models, the project will use the BZ34 well area as an example to carry out fine characterization and interpretation of sand bodies. Fig.10 ), strictly based on the geological interpretation of the attributes, the sand bodies of each parasequence group were characterized. In the sand body interpretation, the sand bodies were qualitatively divided into thinner (light yellow in the figure) and thicker (orange in the figure) according to the relative strength of the amplitude.

[0220] (2.2) Planar distribution characteristics of sand bodies in each parasequence group

[0221] The amplitude distribution in this area should be able to directly reflect the plane development of sand bodies. Stronger amplitudes reflect thicker sand bodies, weaker amplitudes reflect less developed sand bodies, and medium-strong amplitudes generally reflect large sets of mudstones intercalated with thin layers of sand bodies. At the same time, the overall paleo-geomorphology and sedimentary background must be considered. Based on the above analysis results, the plane distribution of sand bodies in different parasequence groups was described.

[0222] 1)PSS1

[0223] The planar distribution characteristics of the PSS1 sand body are that the sand body is generally thick, wide and concentrated. Around wells BZ34-5-1, BZ34-5-2, BZ34-5-3, and BZ34-6-1, the sand body is distributed in a continuous large area, generally trending from southwest to northeast. Near wells BZ34-7-1 and BZ34-3-2D, the sand body is relatively thin, with a relatively small area, and is distributed in a scattered and disorderly small area.

[0224] 2) PSS2

[0225] Compared with PSS1, the sand bodies of PSS2 are thinner, smaller and more dispersed. They are mostly distributed in long and thin strips, generally from southwest to northeast, and are distributed along small rivers. Near well BA34-7-1, the sand bodies begin to change into a disordered network distribution.

[0226] 3)PSS3

[0227] Compared with PSS2, the planar distribution characteristics of the sand body of PSS3 are that the sand body is generally thinner and smaller in area. It is more scattered in the north, but more concentrated in the south. Around BZ34-3-1, the sand body is thinner and distributed in a small area of ​​reticular pattern. Around well BZ34-6-1, the sand body is thinner and mostly distributed in elongated strips, generally trending from southwest to northeast. Near well BZ34-7-1, the sand body gradually thickens, and large-scale sand bodies appear in pieces, showing a disorderly surface distribution.

[0228] 4) PSS4

[0229] Compared with PSS3, the planar distribution characteristics of PSS4 sand bodies are that the overall development of sand bodies gradually becomes thicker, the area increases, and larger surface sand bodies begin to appear. There are fewer sand bodies in the north, mostly in isolated belts or nets, such as near BZ34-1-1 and BZ34-1 S-1. In the middle, the sand bodies are more numerous and concentrated, mostly in a wide belt distribution, generally from southwest to northeast, and there are larger surface sand bodies in the middle of the belt, such as around BZ34-5-1 and BZ34-5-2. In the south, the sand bodies are thinner and more messy, with small blocks of surface, fine belts, and encouraged net distribution.

[0230] 5) PSS6

[0231] Compared with PSS4, the planar distribution characteristics of PSS6 sand bodies are that the sand bodies are generally thicker and the area has increased. They are concentrated in the southwest, with a large number of planar sand bodies. There are fewer sand bodies in the north, mostly in isolated belts or nets, such as near BZ34-1-1 and BZ34-1 S-1. In the southeast, the sand bodies are relatively scattered, mostly in an interlaced net distribution. The sand bodies in the southwest are concentrated, mostly in a wide belt or plane distribution, such as near BZ34-6W-1, where the sand bodies are distributed in a wide belt.

[0232] 6) PSS7

[0233] Compared with PSS6, the planar distribution characteristics of the sand body of PSS7 are that the overall development of the sand body gradually becomes thinner, the area increases, but it is relatively scattered and concentrated in the central and northern parts. There are fewer sand bodies in the north, mostly in small bands or isolated surfaces, such as near BZ34-1-1 and BZ34-1 S-1. The sand bodies in the central and northern parts are larger in area and distributed in a tree-like manner. The sand bodies in the southeast are scattered, mostly in small bands, such as near BZ34-7-1.

[0234] 7) PSS8

[0235] Compared with PSS7, the planar distribution characteristics of PSS8 sand bodies are that the overall development of sand bodies gradually becomes thinner, the area gradually decreases, and it is more scattered. In the north, the sand bodies are thicker and more concentrated, mostly in small bands or isolated surfaces, such as near BZ34-1-1 and BZ34-1 S-1. In the central and northern parts, the sand bodies are relatively thin and very scattered, mostly in small bands or tree-like distribution.

[0236] 8) PSS9

[0237] Compared with PSS7, the planar distribution characteristics of the sand body in PSS9 are that the overall development of the sand body is gradually thinner, the area is reduced, and it is more dispersed. It is basically distributed in small bands or isolated surfaces.

[0238] 9) PSS10

[0239] Compared with PSS9, the planar distribution characteristics of the sand body of PSS10 are that the overall development of the sand body gradually becomes thicker, the area gradually increases, and it is relatively concentrated. In the north, the sand body is thicker and more concentrated, mostly in isolated planes, such as near BZ34-1-1 and BZ34-1 S-1. In the middle, the sand body is relatively thin and very scattered, mostly in small bands. The sand body in the southeast is thinner, but very concentrated, and large blocks of plane sand bodies appear.

[0240] 10)PSS11

[0241] Compared with PSS9, the planar distribution characteristics of PSS11 sand bodies are that the overall development of sand bodies gradually becomes thicker, the area increases, and they are more concentrated. Thick and large-area planar sand bodies appear in the north, middle and south. Most of the sand bodies are distributed in a large-area continuous planar shape. For example, large-area thick sand bodies appear near BZ34-1-1 and BZ34-5-1.

[0242] In general, in the early stage of low-stand + water transgression, the sand bodies are thicker, larger and more concentrated, mostly distributed in a plane, and the entire sand body is in a flower shape. In the late stage of low-stand + water transgression and the early stage of high-stand, the sand bodies gradually become thinner, the area decreases and the distribution is more scattered, mostly in the form of elongated bands and nets, mostly extending east-west. In the late stage of high-stand, the sand bodies gradually become thicker, the area increases, and large-scale massive sand bodies begin to appear, and the distribution is relatively concentrated. The sand bodies have obvious channelization characteristics and the plane is a net-like combination.

[0243] (3) Seismic composite microfacies analysis

[0244] (3.1) Analysis of seismic composite microfacies types

[0245] The detailed characterization of sand bodies and their planar distribution are the basis for seismic-composite microfacies analysis. Because the boundaries and relative thickness of sand bodies mainly come from the mutual fitting of different lithology combinations-sedimentary microfacies combinations-amplitude strengths, especially its planar morphological characteristics provide a "skeleton" for our analysis of sedimentary microfacies. However, due to the limitations of seismic resolution, single sand bodies with thin thickness and multiple interlayered sand bodies are often not characterized. Seismic amplitude is a comprehensive response of a set of sand bodies, and this set of sand bodies may reflect the combination of multiple sedimentary microfacies. Therefore, it is impossible to distinguish each single microfacies when conducting sedimentary microfacies analysis. It is more of a sedimentary microfacies combination-composite microfacies.

[0246] Regional sedimentary facies analysis shows that the BZ34 area is dominated by the outer front of the meandering river delta and shallow lake sediments. Combined with the plane distribution characteristics of the sand body, the composite microfacies in this area can be divided into the following types:

[0247] ① Composite microfacies of distributary channel system. It is dominated by underwater distributary channels, with obvious main channels and relatively well-developed sand bodies, which are often developed in multiple stages. In addition, far sand bars and a few estuary bars coexist with distributary channels, and the sand bodies are relatively thin.

[0248] ② Distributary channel-distant sand bar composite microfacies. The sand body becomes obviously thinner, and the distributary channel is not dominant. It constitutes this type of composite microfacies together with the distant sand bar and inter-bay.

[0249] ③ Distal sand bar-distributary channel composite microfacies. The sand body is relatively thin, with the distal sand bar being dominant, followed by the distributary channel.

[0250] ④ Distal sand bar-sand beach composite microfacies. The sand body is thinner and is mainly composed of distal sand bars, but shallow lake sand beaches are developed in between.

[0251] (3.2) Analysis of distribution characteristics of composite microfacies in different periods

[0252] The three parasequence groups PSS1, PSS3 and PSS11 in the BZ34 well area represent the sedimentation of different periods of the sequence. This paper will take this as an example to illustrate the characteristics of seismic-composite microfacies.

[0253] The PSS1 composite microfacies includes the above three types. The composite microfacies of the distributary channel system is close to the source direction and gradually transitions to the composite microfacies of the distributary channel-distant sand bar and distant sand bar-sand beach towards the center of the basin. Among them, the delta in the southwest extends far toward the basin, and the composite microfacies of the distributary channel system is the most developed.

[0254] PSS3 is located in the sequence lake expansion period, when the relative lake level expands rapidly, the water body is relatively deep, the lake water has little effect on the transformation of the sedimentary sand body, and the sand body is obviously channelized. The sand bodies in the northeast and northwest of the study area are underdeveloped, and the source mainly comes from the southwest direction, with the main microfacies of distributary channel-distant sand bar, followed by the composite microfacies of distant sand bar-sand beach. The composite microfacies of distant sand bar-distributary channel is developed in the eastern part of the study area.

[0255] PSS11 is located at the top of the high stand. With the slow decline of the base level, the sediments gradually advanced toward the basin, and the sand bodies were relatively developed. At this time, the southwest source still dominated. The distributary channel system was very developed in the seismic-composite microfacies, followed by the distributary channel-distant sand bar. In the eastern and southern parts of the study area, obvious distant sand bar-sand beach composite microfacies were developed.

[0256] As a new technology, the present invention can be called seismic microfacies analysis, and its characteristics are as follows:

[0257] ①Seismic microfacies analysis is to explain the results of seismic reservoir prediction in a way that is more in line with sedimentological concepts and theoretical systems, so as to make them more meaningful for causal prediction.

[0258] ② Seismic microfacies is the smallest sedimentary facies unit that can be identified and characterized by seismic reservoir prediction technology. This concept itself determines that its scale varies with the level of seismic resolution and seismic reservoir prediction technology.

[0259] ③The difference between seismic microfacies analysis and seismic reservoir prediction technology is that the core of the latter is how to extract geophysical attribute parameters with more geological significance, and how to use these parameters to more accurately predict sand bodies or other reservoirs. The predicted results are often just very general "sand bodies", and generally do not emphasize the sedimentary genetic significance of these sand bodies or other reservoirs. Their relationship with sedimentary facies units at all levels is not clear, and it is not convenient to use them in lithofacies paleogeographic research. Therefore, they have lost the function of predicting spatial distribution according to the sedimentary facies genetic model. The core of the former is how to interpret these sand bodies more in line with the concept of sedimentology, emphasizing more on the genetic type of sand bodies, and the interpretation results are more in line with geological laws and have more significance for genetic prediction.

[0260] ④ The core of seismic microfacies analysis is to establish a geological-seismic response relationship model under different sedimentary facies backgrounds. There are two methods. One is the statistical method, that is, taking the sedimentary facies area as the unit, the corresponding relationship between the lithologic combination characteristics and different seismic attributes at different control well points is statistically analyzed. On this basis, a relationship plate of vertical sequences of different sedimentary microfacies in each sedimentary facies area is established to optimize the attributes and make the most reasonable seismic microfacies interpretation. The other is the model method. First, in the development area with typical significance, a dense well network is used to carry out parasequence division comparison and sedimentary microfacies analysis, to characterize the vertical superposition law and lateral distribution characteristics of different lithologic combinations, and to establish a fine geological model. Then, the wave impedance characteristics of different lithologies in the modeling area are statistically calculated, the geological model is converted into a wave impedance model, and physical or numerical simulation methods are used for simulation to extract different attributes, thereby obtaining a geological-geophysical response model of a typical sedimentary facies as the basis for the geological interpretation of seismic attributes. The statistical method is simple and easy to implement, and good results can be obtained when there are enough control wells.

[0261] Seismic composite microfacies is a study based on a high-precision sequence stratigraphic framework, so a high-precision sequence framework must be established before microfacies analysis. Based on the study of regional sequence stratigraphy and sedimentary facies, combined with the shallow exploration results of the Yellow River Mouth Depression, the lower strata of the Mingxia section in the three well areas of BZ26, BZ34, and BZ29 were selected as the key target areas and horizons for high-precision sequence and sand body research. Since the BZ34 well area is located in the central position of the depression and is the confluence area of ​​different provenance water systems, it is also taken as the focus of seismic composite microfacies research.

[0262] The present invention has a reasonable concept and can make an interpretation of the sand bodies of seismic composite microfacies under the high-precision sequence stratigraphic framework that is more in line with the concept of sedimentology, more emphasize the genetic type of the sand bodies, and the interpretation results are more in line with geological laws and have more significance for genetic prediction.

[0263] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A sand body characterization method based on high-precision sequence framework seismic and composite microfacies, characterized by , mainly including the following steps: (1) Analysis of sand body geological and geophysical response characteristics under high-frequency sequence framework (1.1) Seismic attribute extraction and optimization; (1.2) Analysis of lithology distribution characteristics; (1.3) Analysis and statistics of the relationship between seismic attributes and lithology at well point locations; (1.4) Distribution characteristics of wave impedance; (1.5) One-dimensional forward analysis of lithology combination, sedimentary microfacies type and amplitude variation; (1.6) Two-dimensional forward modeling based on the comparison of sedimentary microfacies and genetic sand bodies; (2) Seismic attribute characteristics and sand body characterization (2.1) RMS attribute extraction and sand body characterization; (2.2) Characterization of the planar distribution characteristics of sand bodies in each parasequence group; (3) Seismic composite microfacies analysis (3.1) Analysis of seismic composite microfacies types; (3.2) Analysis of the distribution characteristics of composite microfacies in different periods.

2. The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework according to claim 1 is characterized by: The step (1.1) specifically involves extracting a number of attribute maps for each parasequence group in the key well area; through comprehensive analysis of seismic and drilling, accurate calibration of synthetic records is performed to estimate the sedimentary thickness of the target sand body on the seismic, and different time windows are selected to extract attributes.

3. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1 is characterized in that: The step (1.2) is based on the drilling in the study area, statistically analyzing the lithology type, sandstone thickness, lithology combination type, and the relationship between the parasequence group development style and lithology combination in different system domains, and directly applying the statistical results to the analysis of the mutual coupling relationship between the seismic attribute of the well point location-lithology combination and the different lithology combinations-microfacies types-forward characteristics; specifically, it includes the following steps: (1.2.1) Analysis of lithology types and sandstone thickness distribution characteristics; (1.2.2) Analysis of the main lithological combination characteristics under the sequence framework; (1.2.3) Statistics of parasequence group types and their lithological combinations under the system tract framework.

4. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1 is characterized in that: The step (1.3) is to predict the reservoir parameters based on the relationship between the seismic attributes and the reservoir parameters; specifically, it includes the following steps: (1.3.1) Statistical analysis of the relationship between the RMS amplitude between layers of parasequence groups and the lithology of well location; (1.3.2)Statistics of the relationship between Stratimagic seismic facies and lithology.

5. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1, characterized in that: The step (1.4) specifically comprises the following steps: (1.4.1) Analysis of factors affecting wave impedance That is, through the geological information contained in velocity, density and wave impedance, the influence of depth factor, porosity factor and oil and gas content factor on wave impedance is analyzed; (1.4.2) Analysis of distribution characteristics of wave impedance of different lithologies The changing characteristics of wave impedance of oil and gas-bearing sandstone are analyzed in detail from three aspects: velocity, density and wave impedance.

6. The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework as claimed in claim 5 is characterized by: In the step (1.4.2), in order to significantly compare the relationship between the mudstone, siltstone, fine sandstone, oil-bearing sandstone, gas-bearing sandstone and wave impedance in the study area, a lithology wave impedance probability distribution map was established.

7. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1 is characterized in that: The step (1.5) specifically comprises the following steps: (1.5.1) Simple single-layer sand body forward model analysis; (1.5.2) Forward model analysis of a single distributary channel; (1.5.3) Forward model analysis of multi-period diversion channels; (1.5.4) Forward model analysis of lithology combination of sand-mud interbeds (1.5.5) Forward model analysis of distant sand bars and sand beaches; (1.5.6) Forward modeling analysis of composite microfacies of remote sand bar, estuary bar and distributary channel; (1.5.7) Forward model analysis of composite microfacies of distributary channel system; (1.5.8) Analysis of the relationship between oil and gas content and amplitude.

8. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1 is characterized in that: The step (1.6) specifically comprises the following steps: (1.6.1) 2D forward modeling analysis Based on the establishment of earthquake model, forward simulation is realized through wave equation method; (1.6.2) Analysis of spatial distribution patterns of typical sand bodies That is, the vertical distribution pattern of the sand body is delineated by combining seismic and drilling data with plane and section amplitude characteristics; (1.6.3) Analysis of seismic response patterns of typical sand bodies By analyzing the sand body distribution characteristics of typical wells in this area, on the basis of statistical analysis of impedance and lithology combination of existing wells, taking into account the sedimentary environment, lithology, superposition and pinch-out of sand bodies, a geological model consistent with the actual geological conditions is designed for the geological conditions of this area under different conditions. The wave equation method is used for simulation to obtain the geological-geophysical response model of typical sand bodies in key areas. The simulation results are compared with the actual results, and the corresponding parameters of the model are continuously modified to make the simulation results consistent with the actual seismic profiles, thereby obtaining the geophysical response models of various genetic sand bodies under different geological backgrounds.

9. The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework as claimed in claim 8, characterized in that: The seismic wave equation forward modeling algorithm in step (1.6.1) comprises: ①High-order finite difference method The simulation accuracy is improved by increasing the order of the difference equation. Using Taylor expansion, the function f(x) is expanded in the neighborhood of x0: Subtract the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f′(x): Add the above two equations and ignore O(Δx 2 ) The above terms can be used to obtain the second-order accuracy estimate of f″(x): ② Spectral method The Fourier transform technology is used to solve the seismic wave field forward simulation of the wave equation, and the accuracy of the spatial derivative calculation is improved by the properties of the Fourier transform. Using the properties of the Fourier transform, the derivative of the function f(x) can be calculated by the following formula: Taking the acoustic wave equation as an example, the spatial derivative is calculated as follows: The time derivative is calculated using the leapfrog scheme: From this we can get the forward modeling equation:

10. The sand body characterization method based on seismic composite microfacies under a high-precision sequence framework according to claim 1, characterized in that: The step (2.1) is to characterize the sand bodies of each parasequence group by extracting the root mean square amplitude between layers, strictly based on the geological interpretation of the attributes; and in the sand body interpretation, the sand bodies are qualitatively divided into thinner and thicker according to the relative strength of the amplitude.

11. The sand body characterization method based on seismic composite microfacies under high-precision sequence framework according to claim 1, characterized in that: The step (2.2) is to describe the planar distribution of sand bodies in different parasequence groups based on the analysis results in the step (1).

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