Introduction

More and more granite oil-gas reservoirs have been discovered worldwide (Salah and Alsharhan 1998; Plotnikova 2006; Cuong and Warren 2009; Yang et al., 2011; Carvalho et al. 2013; Chen et al. 2018; Du et al., 2019; Ye et al. 2019), which shows great exploration potential for such reservoirs. Meanwhile, the breakthroughs in exploration have greatly promoted research on the structure, reservoir characteristics, and distribution prediction of granite weathering crust.

Currently, some studies have reported on the classification schemes for granite weathering crust (Chen et al. 2016; Huang et al. 2016; Xu et al. 2016; Dou et al. 2015, 2018; Wang et al. 2018; Zhu et al. 2020), and the characteristics of granite reservoirs have also been clarified, which mainly include the physical characteristics of granite, genetic mechanisms, fracture development characteristics, and reservoir reconstructions (Zhou et al. 2005; Yang et al. 2013; Zhu et al. 2013; Li 2016; Xia 2016; Zhao et al. 2019; Ye et al. 2020, 2021). In addition, the main reservoir spaces of weathering crust reservoirs comprise dissolution pores and fractures and varying properties of different structural layers (Song et al. 2011; Xu et al. 2016; Huang et al. 2020; Bai et al. 2021; Du et al. 2021). Further, influenced by geological transformations, a more complex distribution of weathering crust reservoirs is observed (Huang et al. 2016; Guo et al. 2017; Hu et al. 2017; Li et al. 2020; Zhu et al. 2021). Meanwhile, extensive research on the seismic profile features of granite has revealed that ancient granite buried hills exhibit the features of low frequencies and continuous, strong-amplitude reflections compared to the seismic profiles of conventional clastic rocks. There are obvious overlapping reflection wave groups at the strong reflection surfaces, and the underlying bedrock shows discontinuous, weak-amplitude-blank, and disordered reflections (Gong et al., 2010).

The seismic predictions of granite reservoirs have been investigated. The features of seismic wave groups, seismic attributes, and prestack elastic parameter inversions have been the focus of several studies (Chen et al. 2016; Li et al. 2016; Hou 2017; Huang et al. 2017; Wang et al. 2018); however, research on the characteristics of weathering crusts scarce. Thus, current methods are relatively singular, and there has not been an established effective prediction method. Moreover, the relation between the seismic reflection features and weathering crust structures is not properly defined, affording an unclear geological meaning of the seismic reflection characteristics. Hence, the results obtained from only seismic data for studying the distribution of effective reservoirs are unsatisfactory. To solve the above problems, this paper adopts the idea of combining geology and seismology, and fully combines the characteristics of multi-disciplines. On the one hand, an improved Morlet wavelet function is used to process seismic data, which greatly improves the resolution and lays a foundation for the seismic facies research of granite weathering crust. On the other hand, from the perspective of geodynamics, the geological origin of seismic facies in different structural layers of weathering crust is demonstrated in detail, which gives geological meaning to seismic facies and provides a basis for reservoir classification and distribution prediction. Through the full combination of the above two aspects, the problems of incomplete consideration and poor prediction effect of weathering crust reservoir distribution prediction are solved in the past.

The method used in this article has good operability and applicability, as introduced below. Firstly, in terms of technology, Morlet wavelet function is used to process seismic data, which has obvious resolution improvement and strong operability before and after processing. Secondly, in terms of theoretical understanding, from the perspective of geological evolution, the origin of seismic facies in weathering crust is elucidated, and the relationship between seismic and geology is established. The research ideas accord with the geological laws and can effectively achieve the seismic characterization of granite weathering crust and the prediction of effective reservoir distribution.

Geological settings

The Dongying Sag is a substructural unit located in the southeastern Jiyang Depression, Bohai Bay Basin, NE China, with the Chenjiazhuang- Binxian Salient at the north boundary, the Luxi Uplift and Guangrao Salient at the south, the Linfanjia–Qingcheng Salients at the west, and the Qingtuozi Salient at the east (Wang et al. 2010). The study area is in the northern Dongying Sag and includes the Chenjiazhuang Salient, Lijin Subsag, and Binxian Salient (Fig. 1). A series of positive secondary structural units are developed in the sag, and the east-west central fault anticline zone is developed in the deep sag. The structural features of the sag are characterized by few folds and many faults, and faults with different properties and orders of different levels form various types of faults, which combine or compound with each other to form the present complex structure. The basement comprises Archean granite, gneiss, and amphibolite series, with > 10,000 m thickness, and the subsequent strata are mainly deposited on the basement and the four present sets of sedimentary systems are gradually formed.

The target strata studied here mainly comprise the Archean strata, and the outcrop exploration in the Luxi area and drilling results show that granite mainly comprises the Archean bedrock, i.e., monzogranite and granodiorite (Zhang et al. 2017). Till date, 330 wells have been drilled the target strata (Zhu et al. 2021), with varied burial depths, and the drilled depths to the Archaeozoic strata range from tens of meters to hundreds of meters. However, the exploration results for granite reservoirs are not satisfactory because of the diversity of types of granite reservoirs, strong heterogeneity, poor seismic data resolution, and complex reflection characteristics.

Fig. 1
figure 1

(modified from Zhu et al., 2020)

Geological map of the Dongying Sag and study area location.

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Data and methods

Data

Geological and three-dimensional (3D) seismic data were provided by Sinopec Shengli Oilfield Company in Dongying Shan-dong, China. The 3D seismic data cover an area of ~ 1,150 km2, while the geological data are relatively extensive, mainly including oil testing data from 35 wells, 200-m cores from 12 wells, and 120 thin sections from 8 wells. Specifically, the well data mainly include wireline logging curves and logging lithologies from 80 wells and imaging logging from 1 well.

Methods

Methods for improving the seismic data quality, identifying and classifying the seismic facies, and classifying the effective reservoirs are described in this section.

Improving the seismic data resolution

The 3D seismic data in the study area show low resolutions and complex reflection characteristics, and it is crucial to improve seismic data quality. Time-frequency analyses are the best methods to achieve the frequency divisions of seismic signals, which include short-time Fourier transforms, S transforms, and wavelet transforms (Morlet et al. 1982; Stockwell, 1966; Fan et al. 2017). Among them, wavelet transforms can characterize signal changes in both the time and frequency domains and are used to deal with the seismic signals obtained in the study area. The general Morlet wavelet can be expressed as (Morlet et al. 1982):

$${{\rm{\psi }}_0}\;(t)\; = \;{e^{i{\omega _0}{\rm{t}}}}{e^{ - \frac{{{t^2}}}{2}}}$$
(1)

where ω0 is the center angle frequency. Considering that excessive side lobes in the Morlet wavelet will affect the resolution of the frequency division reconstruction of seismic signals, the parameters of the Morlet wavelet function are modified based on the wavelet characteristics of the study area:

$$\Psi \;(t)\; = \;{e^{i{\omega _0}{\rm{t}}}}{e^{ - {3^{{t^2}}}}}$$
(2)

Compared with the Morlet wavelet before modification, the modified Morlet wavelet has only one pair of side lobes (three phases) in the time domain, and its waveform is similar to that of the Ricker wavelet; however, its frequency is higher than that of the Ricker wavelet (Fig. 2). Thus, a wavelet function whose waveform is near that of the observed seismic wavelet can improve the processing results when using wavelet transforms (Tao et al. 2015). The modified Morlet wavelet is used to transform the ideal signal (e.g., Ricker wavelet) and has a narrower bandwidth than the original Morlet wavelet, reducing the interference from excessive side lobes in the following spectrum reconstruction (Fig. 3). Decreasing the number of wavelet side lobes for improving the quality of seismic data has been used in many other fields of research with good results (Liu et al. 2016; Qi et al. 2016; Yang et al. 2018).

Fig. 2
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Characteristics of the Morlet wavelet in the time domain. (a) Characteristics of the Morlet wavelet in the time domain before modification; (b) characteristics of the modified Morlet wavelet in the time domain

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Fig. 3
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(a) Theoretical Ricker wavelet signal; (b) Morlet wavelet time–frequency analyses results before modification; (c) modified Morlet wavelet time–frequency analyses results

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Identification and division of granite seismic facies

Seismic facies are reflecting units with specific reflection characteristics that are different from the reflection characteristics of adjacent areas and exhibit the seismic response characteristics of specific geological bodies or sedimentary facies (Sangree et al., 1979; Deng 2004). From the seismic data that are processed by frequency division reconstruction, the representative seismic profiles of granite weathering crust are investigated. Subsequent statistical analysis of the relations among different seismic reflection characteristics and amplitude values is performed. Further, the granite seismic facies are classified based on seismic amplitude and seismic refection morphology.

Classification of effective reservoirs

The internal reflection characteristics of weathering crusts are complex. To clarify the geological meanings of the different reflection characteristics, a comprehensive analysis incorporating well data was performed. In brief, (1) the weathering crust structures are classified according to the Zhu et al. (2020) scheme. (2) Well-seismic calibrations are performed to clarify the corresponding relation between the seismic facies and granite weathering crust structures. (3) From the calibration results, the effective reservoirs are classified based on the evolution process of the weathering crust and reservoir space, porosity and permeability, conventional logging, imaging logging, and oil-bearing data.

Results

Improved resolution of seismic data

A dominant frequency occurs in frequency division and seismic data reconstruction processes (Wang et al. 2001). Seismic data resolution at this dominant frequency is the highest and the details of seismic reflections are the clearest. The dominant frequency can be determined as follows. (1) To determine peak frequency, the frequency spectrum of the target layer is analyzed; (2) according to the peak frequency, the frequency division experiment is performed from low to high frequencies over the range of effective frequency bands; (3) the inflection point of the dominant frequency is determined experimentally. When the frequency is lower or higher than the dominant frequency, the seismic data resolution decreases. (4) The dominant frequency is supposedly the frequency at the inflection point.

Spectral analysis of seismic data of the Archean strata shows a peak frequency of 22.5 Hz for the granite reservoir. According to the peak frequency, the 10–75 Hz frequency division processing experiment is performed in the effective frequency band. Dominant frequency of Archean strata is set to 30 Hz as the test revealed the best resolution at a test frequency near 30 Hz, which is ∼1.3 times the peak frequency of the actual seismic data. Improved seismic data resolution at the dominant frequency is found along with clearer internal seismic reflection characteristics of granite (Fig. 4).

Fig. 4
figure 4

Comparison of the frequency division reconstruction effects of the seismic data for the granite in the study area. (a) Original seismic profile through well Z379; (b) seismic profile through well Z379 processed by frequency division; (c) original seismic profile through well Cq10; (d) seismic profile through well Cq10 processed by frequency division

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Classification and distribution of seismic facies

Classification of seismic facies

The granite seismic facies are classified into strong-amplitude facies, medium-amplitude facies, and weak-amplitude-blank facies based on seismic refection morphology and the distribution range of the seismic amplitudes (Fig. 5).

Fig. 5
figure 5

Classification and characterization of typical seismic facies of granite

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Strong-amplitude facies exhibits strong amplitudes and highly continuous seismic reflection, with amplitudes ranging from 23,700 to 32,800. As a reflecting layer located on top of the granite, it has a smooth surface and a thin thickness, relating to two seismic events. The reflection characteristics are obviously different from those of the overlying sedimentary strata and indicate that the geological strata are parallel, the tectonic activity is weak, and tectonic fractures are not developed.

The medium-amplitude facies has clearly lower amplitudes than the strong-amplitude facies in the range of 5,250 − 24,000. These facies are mainly characterized by parallel to subparallel reflections and layered reflections, and the continuity of the seismic events is generally poor.

The weak-amplitude-blank facies is characterized by weak internal reflecting interfaces with amplitudes in the 0–5,330 range. Compared with the overlying sedimentary strata, the acoustic impedances considerably increase, and the seismic wave velocities are the largest, revealing that the geological body is dense, and its lithology is uniform and that structural fractures are not well developed. This type of seismic facies is relatively stable and can develop in different depth ranges in the study area.

Distribution of seismic facies

(1) Profile distribution

Herein, based on seismic refection morphology (continuity, frequency) and the distribution range of the seismic amplitudes, a 10 × 10 interpretation survey (one seismic profile is interpreted every 10 survey lines, and the interval between survey line is 12.5 m) is used for the analysis of the distribution of granite seismic facies. The strong-amplitude facies is distributed on the gentle slopes located close to the structural high of the Chenjiazhuang–Binxian Salient in the study area and shows clearly different reflection characteristics relative to those of the overlying sedimentary strata. The medium-amplitude facies is distributed on the slopes with a relatively deep depth between the two uplifts, while the weak-amplitude-blank facies is widely distributed at different elevations (Fig. 6).

Fig. 6
figure 6

Profile distribution of granite seismic facies. The profile location is shown in Fig. 1

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(2) Plane distribution

The profile-plane combination method is used to study the plane distribution of seismic facies. The strong-amplitude facies is distributed in the north, northeast, and southwest, with burial depth < 1,500 m. The medium-amplitude facies is developed in the central section, with relatively deep stratum, which exhibits the characteristics of east-west strip distribution. The weak-amplitude-blank facies is widely distributed and can develop at different altitudes (Fig. 7).

Fig. 7
figure 7

Plane distribution of granite seismic facies

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Distribution of seismic attributes

The granite reservoirs have relatively deep burial depths, and the high-frequency signals have higher attenuation levels than the low-frequency signals in the seismic data, making the extraction of reservoir attributes challenging. According to research, a dominant frequency band is present in the frequency division processing of the Ricker wavelet, within the dominant frequency band, the maximum amplitude energy of the Ricker wavelet is the highest, the shape is clear, and the energy near the main frequency is compensated, affording more authentic seismic data (Yang et al. 2018). Hence, at the dominant frequency, the attribute of maximum amplitude can be used as a sensitive attribute to extract the distribution of granite reservoirs.

Granite weathering crust is proposed to be vertical zoning; thus, the seismic attributes are extracted using different time windows. First, a (Tg, Tg + 30 ms) time window, where Tg is the top of the Archean, is defined on top of the granite to extract the top seismic attribute features. The results show that there are three types of maximum amplitude attribute on top of the granite based on energy intensity, namely, strong amplitudes, medium amplitudes, and weak amplitudes. The strong amplitudes are distributed in the southwest and north portions, the medium amplitudes are distributed in the middle area with a strip distribution, and the weak amplitudes are distributed in the southeast and northwest portions (Fig. 8). Generally, the distributions of the seismic attributes on top of the granite are consistent with the plane distribution of the seismic facies. Subsequently, the attributes in the middle of the weathering crust are extracted using the time window of (Tg + 75 ms, Tg + 120 ms). The newly extracted attribute map shows medium amplitudes and weak amplitudes as the only seismic attributes. The medium amplitudes are distributed in the west and northeast portions with a strip shape, while the weak amplitudes are widely distributed in the southeast, northwest, and north parts of the study area (Fig. 9).

Fig. 8
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Attribute map of the maximum amplitudes at the top of granite (time window Tg, Tg + 30 ms)

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Fig. 9
figure 9

Attribute map of the maximum amplitudes in the middle of granite (time window Tg + 75 ms, Tg + 120 ms)

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Types of effective reservoirs

The seismic facies is correlated with the structures of the weathering crust by the seismic-well tie method. Based on reservoir spaces, porosity, permeability, and well logging and oil-bearing characteristics, the effective reservoirs of granite are evaluated, i.e., type I (medium-amplitude facies reservoirs), type II (strong-amplitude facies reservoirs), and type III (weak-amplitude-blank facies reservoirs) (Fig. 10).

Fig. 10
figure 10

Classification and characterization of effective reservoirs of granite

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Type I reservoir shows good, layered reflections on the seismic profiles and represents the dissolution layer. Based on the calibration results, the medium-amplitude facies has obvious traces of dissolution in the cores and dissolved pores and fractures form the reservoir space. In some cores, two sets of intersecting fractures can be observed. High-angle dissolved fractures can also be seen in the image logging data. Zhu et al. (2020, 2021) specified an average porosity of 4% of the reservoirs in the areas with a developed dissolution layer in the study area and a permeability of 0.5 mD. In addition, in the conventional logging data, strongly fluctuating curves of the acousticlog (AC) and laterolog deep (LLD) are observed. Based on the oil test and logging interpretation data, the areas where type I medium-amplitude facies have developed, weathering crust intervals are commonly the oil-bearing layer or water-bearing oil layer and exhibit high oil and gas productivities. For instance, well Z14, which is located in the Wangzhuang oilfield in the north-central part of the study area, is characterized by medium-amplitude reflections in the intervals of 1,532-1,896 m. This well produces nearly 50 t of oil per day.

Type II reservoir represents eluvium. The calibration results reveal that in the areas with strong-amplitude facies development, the lithology mainly comprises sandy gravel, the rock is considerably broken, the rock structure has been destroyed. The core and imaging logging data show that the reservoir space mainly comprises dissolved pores and fractures. The average porosity of the reservoirs is 4%, and the permeability is 1 mD (Zhu et al. 2020, 2021). The LLD values are small, the AC values are large, the shapes of the LLD and AC logging curves are gentle, and the curves only fluctuate locally. Furthermore, according to the oil test and logging interpretation data, the areas where type II strong-amplitude facies have developed, weathering crust intervals are commonly poor oil layer and aquifer and exhibit very poor oil and gas productivities. For instance, in well S87, which is located in the southwestern part of the study area, there is an oil patch in the cores obtained from the strong-amplitude facies. However, no oil can be produced during oil testing.

Type III reservoir represents a disintegration layer. The calibration results reveal that in areas with weak-amplitude-blank facies, the rock density is very high and low weathering and blocky characteristics are obvious. Structural, joint, and high-angle dissolved fractures can be seen occasionally in cores, and continuous and discontinuous conductive fractures can be observed in image logging. This indicates that the reservoir spaces of type III reservoirs comprise fractures of various origins. Previous works proposed that these reservoirs have an average porosity and permeability of 2% and 0.11 mD, respectively (Zhu et al. 2020, 2021). The conventional logging curves are characterized by high LLD values and low AC values, and curve fluctuations are not obvious. Further, the amplitudes of the logging curves are generally stable. Furthermore, the oil test and logging interpretation show that in the areas with weak-amplitude-blank facies development, the weathering crust reservoirs mainly correspond to water layer or dry layer. In well C18, which is located in the shallow portion of the northern study area, the test results show that there is no oil production in areas with weak-amplitude-blank facies development.

Discussion

Origin of seismic facies

Previous studies on the seismic facies of granite buried hills revealed that the reflections from the top surfaces of the buried hills are strong, with good continuity and low frequency. Further, there are intermittent reflections under strong reflections, while the reflections within the buried hills are disordered and comprise weak or blank reflections (Deng and Peng 2009; Gong 2010; Deng 2015; Wang et al. 2018; Song et al. 2020; Sun et al. 2020). However, the origins of the different seismic reflection characteristics have not been extensively explored. Currently, Zhu et al. (2020) have proposed a division scheme for granite weathering crusts. This division scheme clarifies the genetic mechanism of granite weathering crusts. With gradual weathering, the early disintegration layer evolves into a dissolution layer, and then into a sandy residual layer, and finally the top eluvium is denuded. Each layer of the weathering crust evolves from the original granite. Consequently, the longitudinal evolution structure of weathering crust is formed (Fig. 11).

Fig. 11
figure 11

(modified from Zhu et al. 2020). Note The unweathered layer does not belong to the weathering crust structure

The longitudinal evolution structure model of granite weathering crust.

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In the light of this division scheme, the outcrop, cores of 12 wells as well as logging data of 80 wells and seismic data are used for the analysis of the longitudinal structural characteristics of granite weathering crust. The results show three types of longitudinal superposition of the weathering crust: disintegration layer (Fig. 12-a), eluvium-disintegration layer (Fig. 12-b), and dissolution layer- disintegration layer (Fig. 12-c). The diversity of longitudinal superposition types of weathering crusts shows that this is a division scheme that fully considers the evolution process and reveals the complexity of weathering crust evolution.

Fig. 12
figure 12

Superposition types of the longitudinal structure of granite weathering crust. M. Dissolution layer, M/. eluvium, N. disintegration layer. (a) Type of disintegration layer; (b) superposition type of eluvium-disintegration layer; (c) superposition type of dissolution layer-disintegration layer

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From this proposal (Zhu et al. 2020), core observation from 12 wells is examined, and an obvious evolutionary relation between different structures of granite weathering crust is revealed (Fig. 13). Hence, we speculate that the weathering crust experiences different weathering degrees, and the internal structure and physical properties of rocks are obviously different, affording different reflection characteristics of the weathering crust. To verify this hypothesis, according to the previously mentioned division scheme (Zhu et al. 2020), we study the longitudinal structures and transverse variation of the weathering crust in some wells containing cores. The longitudinal structures of granite weathering crust in different structural zones exhibit regular changes. Generally, the weathering crust at high position comprises a disintegration layer and the weathering crust in the middle and low parts comprises a multitype double-layer structure (Fig. 14a). Specifically, well C34, which is located in the high part of the basement retains only a disintegration layer, and the cores are featured by high density with obvious blocky characteristics (Fig. 14b). In well Z366, the weathering crust exhibits an eluvium-disintegration layer structure. The eluvium at the top is thin, and the rock is loose and ruptured. The rock structure of the disintegration layer in the lower part is well preserved, which shows two obvious layers in the vertical direction (Fig. 14c). In well Z362, the weathering crust is divided into a dissolution layer and a disintegration layer in the vertical direction. In the cores, the dissolution layer at the top develops dissolution fractures, while the disintegration layer in the lower part is relatively tight overall and the original characteristics are well preserved (Fig. 14d). In addition, Fig. 14a reveals that the geomorphology of the basement top has an obvious controlling effect on the transverse variation of granite weathering. Specifically, the higher the altitude, the stronger the weathering and denudation, and the previously formed weathering crust structure has been denuded, leaving only the underlying fresh disintegration layer. With decreasing altitude, the weathering is weakened, and an eluvium and a dissolution layer gradually appear. Altitude and weathering affect the distribution of granite weathering crust, and ultimately complicate the transverse variation of weathering crust. Therefore, the proposed hypothesis is reasonable.

Fig. 13
figure 13

Evolution relation between different structures in granite weathering crust

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Fig. 14
figure 14

Longitudinal structures and distribution characteristics of weathering crust and core characteristics of some wells. (a) Longitudinal structure and transverse variation of weathering crust at different structural locations; (b) core characteristics in well C34; (c) core characteristics in well Z366; and (d) core characteristics in well Z362

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Figure 15 shows a good correspondence between the seismic facies and each structural layer of the granite weathering crust. In particular, strong-amplitude facies corresponds to eluvium. The cores from the eluvium section mainly comprise sandy gravel and mixed argillaceous deposits and are loose and broken. Further, dissolved pores as well as dissolved fractures are relatively developed in thin sections (Fig. 15). In addition, the values of LLD and AC present a negative and positive anomaly, respectively. The overall shape of the LLD logging curve is gentle, while the shape of the AC logging curve shows a strong fluctuation. Moreover, the development depths and distribution characteristics of the eluvium section are studied along with the relation between weathering and elevation (Zhu et al. 2021). Eluvium is considered to have entered the late stage of weathering crust evolution and the rock structure has been destroyed, indicating considerably improved properties of eluvium. Thus, strong-amplitude reflections are caused by the strong weathering of eluvium owing to the great difference between the physical parameters inside the rock and the overlying sedimentary rock stratum, and an interface with high acoustic impedance contrast is formed, presenting the characteristics of low frequency and continuous strong-amplitude reflection in the seismic profiles.

Fig. 15
figure 15

Response relation between seismic facies types and granite weathering crust structures, cores, thin sections, and logging data

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The medium-amplitude facies corresponds to the dissolution layer. The dissolved pores and fractures observed in the cores and thin sections are well developed (Fig. 15). In addition, the LLD values and AC values jump clearly in the section containing the dissolution layer, and the curve shapes fluctuate greatly, clearly indicating that the properties of the dissolution layer have been improved. Previous studies have shown that primary pores in granite reservoirs do not dominate while their physical properties are considerably improved owing to dissolution and faulting, forming dissolution pores and fractures (Liu et al. 2014; Chen et al. 2016; Huang et al. 2016; Zhang et al. 2017). Thus, the dissolution layer represents a moderate weathering, and the physical properties of rocks have been considerably improved. However, unlike eluvium, a relatively complete rock structure of the dissolution layer is observed, while on the seismic, this layer exhibits layered reflections that are characterized by medium amplitudes. In other words, medium-amplitude facies are caused by a dissolution layer being in a middle stage of weathering owing to transformation by geological processes; many dissolved pores and fractures are formed in rocks and physical properties are considerably improved. Thus, this facies has characteristics of layered discontinuous and medium-amplitude reflections in the seismic profiles.

The weak-amplitude-blank facies represents a disintegration layer (Fig. 15). Massive features are clear in the cores, and there are few signs of weathering transformation. Further, fractures are not dominant in the cores. In the thin sections, there are complete mineral forms and clear boundaries. In the logging data, very small AC values but very large LLD values are observed. The shapes of the AC and LLD logging curves are generally gentle and only fluctuate locally, indicating poor physical properties and a low transformation degree. According to the abovementioned analysis, the disintegration layer is in the initial stage of weathering, the rock mass structure is well preserved, and the interior of the rock mass is highly dense and exhibits clear block characteristics. In particular, the weak-amplitude-blank reflections are caused by the disintegration layer being the early stage of weathering and experiencing less weathering and dissolution. The rock is relatively tight with a homogeneous internal structure and massive general structure. Hence, there are basically no reflecting interfaces or the reflecting interfaces are not clear in the seismic profiles, which is manifested as weak-amplitude-blank facies.

According to the discussion, the distribution pattern of the relationship between seismic facies and top structure of weathering crust is established. In Fig. 16, we can observe that the formation and distribution of weathering crust are closely related to altitude. After different degrees of geological evolution (the higher the altitude, the stronger the weathering, the worse the preservation effect), weathering crust structure shows many kinds of superposition in the longitudinal direction and also exhibits differences in horizontal distribution. That is, with the decrease of elevation, the structure of top of the weathering crust gradually changes from disintegration layer to eluvium and dissolution layer. Correspondingly, according to the calibration results of seismic facies and weathering crust structures, the lateral distribution of seismic facies also shows a certain regularity with the decrease of altitude. namely, with the gradual decrease of the altitude, the seismic facies at the top of the weathering crust gradually change from weak amplitude – blank facies to strong amplitude facies and medium amplitude facies. This model not only clarifies the relationship between seismic facies and weathering crust structure, but also clarifies the distribution characteristics of different seismic facies, which is helpful to understand the geological origin of seismic facies of weathering crust.

Fig. 16
figure 16

Distribution pattern of relationship between seismic facies and top structure of weathering crust

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Distribution of effective reservoirs

Some studies have reported the distribution patterns of granite reservoirs (Wang et al. 2016; Hu et al. 2017; Zhu et al. 2021). However, the existing distribution patterns are mainly based on a static perspective and do not consider the fact that the weathering crust has been undergoing evolution for a long period of time. Thus, the distribution of effective reservoirs is highly complex, and the results of previous studies are not applicable to the study area.

Although the relations among the types of effective reservoirs, weathering crust structures of granite, and seismic reflection characteristics are clarified, the distribution characteristics of the seismic facies cannot simply be used to characterize the distribution characteristics of effective reservoirs. Because they are affected by the interpretation accuracy, it is difficult to accurately determine the boundaries among different seismic facies. For instance, the comparison results between the distribution characteristics of seismic facies and the seismic attributes show that they are generally consistent; however, there are differences in some areas, and these occur especially at the boundary of two seismic facies, making the distribution differences clearer.

Hence, through seismic facies analysis and sensitive attributes interpretation, the characteristics of weathering crust cross-well sections in different directions and at different elevations, and the results of well-seismic calibration, the distribution of effective reservoirs of granite can be determined comprehensively. Notably, in the areas with exploration wells, the effective reservoir types depend on the features of weathering crust in the boreholes. In the areas without exploration wells, especially at seismic facies boundaries, the features of effective reservoirs mainly refer to the attribute map.

Figure 17 shows that type I effective reservoir is distributed in the western slopes, with an elevation of 1,300-2,500 m, which is mainly located in the medium-amplitude facies development area; type II effective reservoir is mainly distributed in the southeast and north slopes of the study area, with a relatively limited range, and the elevation is mostly below 1,500 m, and mainly corresponds to the strong-amplitude facies development areas, and type III effective reservoir is widely distributed at various elevations.

Fig. 17
figure 17

Distribution of effective reservoirs in granite weathering crust

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Exploration of favorable reservoirs

Several granite oil fields have been found worldwide (Ma et al. 2006; Deng 2015; Xue et al. 2015; Xia 2016; Hu et al. 2017). In general, granite oil-gas reservoirs are characterized by upper generation and lower storage, namely, oil and gas are mainly supplied by the source rocks in the overlying strata. Currently, the medium-sized Wangzhuang oil and gas field and small-sized Shanjiasi oil and gas field have been found respectively in the north-central part and southwestern part of the study area. Research results reveal that oil source is from the source rocks located in the overlying strata, and the reason for the differences in reservoir size is the different reservoir formation models (Zhu et al. 2021). Moreover, physical properties as well as preservation conditions of reservoirs also affect their hydrocarbon accumulation scales. It has been shown that in the geological evolution process, the earlier the reservoir is preserved, the better is the development of the reservoir. The properties of reservoirs that are located on slopes with relatively low altitudes are better (Zhu et al. 2021), which demonstrates that the physical reservoir properties and preservation conditions are important for hydrocarbon accumulations.

Based on the above analysis and the following two considerations, the distribution of favorable reservoirs is determined. First, the oil-bearing characteristics of different seismic facies at different elevations are analyzed, and the results show that oil-bearing characteristics of effective reservoirs are closely related to the elevations and seismic facies types. In particular, oil-bearing characteristics of reservoirs of the medium-amplitude facies in a relatively low-altitude area is considerably better than those of the weak-amplitude facies in a relatively high-altitude area. For instance, in well Z14, the depth range of 1,532-1,896 m comprises the medium-amplitude facies, and the oil test results indicate an oil production of 1,200 t/d associated with a typical high-yield well. For well Z39, the elevation is slightly higher than that of well Z14, and the oil test results show > 10 tons daily oil production associated with a medium-high production well, which corresponds to the medium–weak-amplitude facies; however, in well C18 with a high altitude, the target interval is the blank facies, and the oil test results show that no oil is produced. Second, the medium-sized Wangzhuang oil field of the study area is analyzed, and the hydrocarbon accumulation pattern is clarified. The results show that the oil–gas accumulation model of the reservoir mainly comprises a source–crust connected type, i.e., the source rocks directly overlay the granite reservoir and has good oil- gas properties. In addition, granite reservoirs exhibit medium-amplitude reflections, and the elevation of the trap is ~ 1,500 m.

From the characteristics of the discovered reservoirs combined with the oil testing data and effective reservoir distribution characteristics, the exploration strategy for favorable reservoirs is defined, i.e., medium-amplitude facies in a relatively low altitude area is the most favorable reservoir exploration areas for granite. The reservoirs in these locations exhibit good physical properties as well as direct contact with the overlying source rocks, which provide good conditions for hydrocarbon accumulations over short distances. In addition, the favorable preservation conditions provide reliable conditions for the formation of large- and medium-sized oil and gas fields.

Conclusions

In this paper, considering the current situation of the low resolution of seismic data and the diversity of reservoir types as well as the complexity of distribution, a novel effective method based on seismic and geological data has been used to study the seismic reflection characteristics and distribution of effective reservoirs in granite weathering crust. The following conclusions are derived:

(1) The improved Morlet wavelet function can be used to improve the resolution of seismic data from granite weathering crust, and the application effect is good.

(2) Affected by differences in weathering, the seismic facies in granite weathering crusts can be divided into three types longitudinally: strong amplitude facies, medium amplitude facies and weak-amplitude-blank facies, which correspond to the late, middle and early stages of weathering crust evolution respectively.

(3) Effective reservoirs can be divided into three types. Specifically, type I effective reservoir corresponds to the medium amplitude facies (dissolution layer), type II effective reservoir corresponds to the strong amplitude facies (eluvium), and type III effective reservoir corresponds to the weak-amplitude-blank facies (disintegration layer). The distribution of effective reservoirs is obviously affected by the elevation.

(4) The areas where medium-amplitude facies have developed are the most favorable reservoir exploration zones for granite with good conditions for hydrocarbon accumulation and thus can be explored first.