Quantitative identification of triassic top unconformity: vertical structure and its reservoir significance in the sanbian area of the ordos basin

Abstract

The Triassic top unconformity in the Ordos Basin, which serves as a transfer station for hydrocarbon migration, has become a bottleneck for Mesozoic oil and gas exploration. Taking the Sanbian area as an example, based on core observations, petrophysical properties, and a weathering index analysis of five coring wells, a standard for the quantitative identification of the vertical structure of the unconformity is established using the optimal segmentation method and principal component analysis of conventional logging curves. The standard is then applied to 40 real wells, and 32 typical unconformity reservoirs are dissected. The results show that the reclassification of the unconformity surface corrects the 17.5% error in the geological stratification as an unconformity. On this basis, a quantitative identification standard for the structure of the unconformity is established via the principal component curve. The analysis of unconformity structure types applied to five paleogeomorphic units reveals that the slope mouth and slope develop three layers of structure, namely residual layer, weathered clay layer, and weathered leaching zone, while highlands, river valleys, and inter-river hills lack weathered clay layer. As an independent oil and gas-bearing layer, the unconformity has two types of reservoir-forming models. The first is the hydrocarbon accumulation in the Chang1–Chang2 member shielded by weathered clay layer in the slope mouth and slope. The second is hydrocarbon migrated from the residual layer to the local structural high part of the Yan 10–Yan 9 member in the slope mouth. The hydrocarbon in the unconformity is complementary to the upper Yan 10–Yan 9 member and the lower unweathered rock layer of Yanchang Formation. The results of this study are of great significance to the quantitative identification of unconformity structures in exploration wells without coring data in the study area, as well as to future hydrocarbon exploration in the Mesozoic strata.

Keywords

Triassic top unconformity paleogeomorphology vertical structure quantitative identification hydrocarbon exploration Sanbian area

Introduction

An unconformity is a sedimentary discontinuity that records crustal uplift, weathering, and denudation events (Miall, 2016). Such discontinuities are widely used in basin analysis, stratigraphic correlation, mineral exploration, and other fields. An unconformity can not only serve as an active zone of ore-bearing fluids (Hurtig et al., 2014; Zenghua et al., 2017), but also serve as a good migration channel and location for the accumulation of hydrocarbons (Wu et al., 2012; Gao et al., 2013; Wang et al., 2019; Zhang et al., 2020). Currently, approximately 20% to 30% of reservoirs discovered worldwide are oil and gas reservoirs related to unconformities (Pan, 1983; He, 2007; Miall, 2016; Zhang et al., 2020). An unconformity is not a simple surface but a geological body with a complex three-dimensional structure (He, 2007). A clastic unconformity is generally composed of a residual layer (e.g. a bottom conglomerate or water-bearing sand body) above the unconformity surface and a paleo-weathering crust (subdivided into a weathered clay layer and a weathered leaching zone) below the unconformity surface (Wu et al., 2003; Song et al., 2010; Zou et al., 2014). At present, there are four methods for identifying unconformity structures in clastic rocks. The first is qualitative analysis conducted based on observations of geological sections and cores in the field (Zhao et al., 2009; Wu et al., 2012).

The second method is quantitative analysis conducted based on limited petrophysical property testing and rock element contents (Zou et al., 2014); the element content method can be divided into the trace element method and the major element weathering index method (Zhao et al., 2009). The third method is restoration of the paleogeomorphology of the unconformity by means of the impression method and the residual thickness method (Song et al., 2003; Guo and Sun, 2006). The fourth method involves using conventional logging curves. The traditional method is qualitative classification based on the shape of the curve (e.g., finger, box, and sawtooth) and the presence of amplitude difference (Wang and Yang, 2010), which has no unified reference standard. This method is significantly influenced by the experience of researchers, and it is difficult to compare different research areas. Based on this, later studies developed the quantitative division of unconformity structures using multivariate statistical methods (Zhao et al., 2007; Chen et al., 2010; Zhang et al., 2020). Of these four methods, methods 1 and 2 have high costs and limited data, so they cannot be widely used. Method 3 is the most widely used in the study of the Triassic top unconformity in the Ordos Basin thus far. On the basis of the restoration of the paleogeomorphology of the unconformity, the spatial relationship between the paleogeomorphology and the sedimentary sand bodies and the paleogeomorphological reservoir types and reservoir forming models have been discussed (Zhu et al., 2010; Bu et al., 2019; Zhang et al., 2019). Only a few researchers have preliminarily applied method 4 to identify the location of the Triassic top unconformity and discuss the physical properties of the pre-Jurassic clastic weathering crust (Ding and Zhang, 2010; Li et al., 2017). However, no systematic qualitative and quantitative identification of this unconformity's three-dimensional structural layer has been conducted. With the development of oil and gas exploration in the study area in recent years, it has been found that the migration and adjustment of the oil and gas from the Triassic to the Jurassic cannot be reasonably explained by studying only the surface structure of the paleogeomorphology (Fu et al., 2013; Li et al., 2020; Zhang et al., 2022), and the Triassic top unconformity, as the transfer station in the oil and gas migration, has become a bottleneck for Mesozoic oil and gas exploration. The further quantitative identification of the spatial distribution of the unconformity structure based on its paleogeomorphology and subsequent analysis of its contribution to hydrocarbon migration and accumulation are key problems that urgently need to be solved.

In this study, based on observations of cores from existing coring wells, petrophysical properties, and a weathering index analysis of the Triassic top unconformity in the study area, several logging curves were selected, a multivariate statistical method was used to determine the depth of the unconformity surface, and a quantitative classification standard for the unconformity's vertical structural layer was established. The data from 40 wells were processed according to this standard and 32 typical reservoirs were analyzed to reveal the spatial distribution of the unconformity's structure in the different paleogeomorphological units. In addition, the controlling influence of the unconformity on the formation of the upper and lower reservoirs and the hydrocarbon accumulation pattern was investigated. The results of this research provide a quantitative standard for the classification of unconformity structures in exploration wells without coring data in the study area, and they provide theoretical guidance for future petroleum exploration in the Mesozoic strata of the study area.

Geologic setting

The Sanbian area is located in the Midwestern part of the Yishan slope in the Ordos Basin. It was named the Sanbian area because it geographically includes Anbian, Dingbian, and Jingbian, from west to east. The regional tectonic background is a gentle monocline with a westward dip and an area of 9850 km² (Figure 1).

Figure 1.

(a) and (b) Location and tectonic units of the Ordos Basin; (c) paleogeomorphology of Triassic top in the Sanbian area of the Ordos Basin.

The Upper Triassic Yanchang Formation in the Ordos Basin experienced the formation, peak, and decline of large lake basins, during which a set of sandy clastic rocks with a thickness of about 1400 m was deposited (Zhu et al., 2010). These rocks can be divided into 10 sections, the Chang 10 to Chang 1 sections, from the bottom to the top. At the end of the deposition of the Yanchang Formation, influenced by the Indosinian movement, the entire basin was uplifted, the top of the Yanchang Formation was subjected to weathering, denudation, and river erosion, and the strata were lost to varying degrees. This formed the pre-Jurassic paleogeomorphology, which was characterized by widely distributed water systems, crisscrossing gullies, and undulating hills (Song et al., 2003; Guo and Sun, 2006). The western part of the Sanbian area was seriously eroded by the ancient MengShan and GanShan rivers, while the central and eastern parts were dominated by weathering and denudation (Figure 1(c)). The strata of the Jurassic Fuxian Formation and Yan'an Formation were deposited on this ancient denudation landform. The formations are composed of clastic rocks with a thickness of about 600 to 800 m. The Yan'an formation can be divided into 10 sections, the Yan 10 to Yan 1, sections from the bottom to the top. Thus, a regional unconformity was formed between the Triassic Yanchang Formation and the Jurassic Fuxian and Yan'an formations; this uncomformity is generally called the Triassic top unconformity (Fu et al., 2013) (Figure 2).

Figure 2.

Comprehensive histogram of strata in the Sanbian area of the Ordos Basin.

The pre-Jurassic paleogeomorphology formed by the Indosinian movement determined the development scale of the unconformity's weathering crust and the deposition of the lower strata of the Fuxian and Yan'an formations. The thickness of sections Yan 9 and above is not significantly different, making it a normal deposit. The strata of Fuxian Formation and the Yan 10 section are river filling deposits that fill and complete the pre-Jurassic paleogeomorphology, and their accumulated thickness has a mirrored relationship with the pre-Jurassic paleogeomorphology. The thickness and lithology changes are records and impressions of the pre-Jurassic paleogeomorphology (Song et al., 2003; Zhu et al., 2010). Therefore, the pre-Jurassic paleogeomorphology can be inverted based on the stratum thickness of the Fuxian Formation and the thickness of Yan 10 (Figure 1(c)). The paleogeomorphology is divided into five units: the river valley, inter-river hill, slope mouth, slope, and highland units. Based on the distribution position, the river valley was the lowest, while the slope mouth, slope, and highland formed around the river valley from low to high on both sides. The inter-river hill was an isolated residual hill in the river valley. In terms of area, the river valley, slope mouth, and slope area were larger, while the highland area was smaller and has become an obvious denudation area in the northern part of the Chengchuan area and the western part of the Jinjiwan area (Figure 1(c)).

The source rock of the Mesozoic crude oil in the study area was primarily the Chang 7 member of the Yanchang Formation (Zhao, 1996), which began to generate hydrocarbons in the late Middle Jurassic to Late Jurassic, and the hydrocarbons began to mature and migrate on a large scale in the middle and late Early Cretaceous. The Triassic top unconformity had an important influence on the migration and adjustment of the hydrocarbons from the lower Triassic to the Jurassic in the study area, as well as the hydrocarbon accumulation in Chang 1, Chang 2, the Fuxian Formation, and part of Yan 10 (Fu et al., 2013; Shi et al., 2014).

Methods

Data collected by the Research Institute of Exploration and Development of the Changqing Oilfield Company, PetroChina, including core, well logging, petrophysical testing, and oil and gas testing data, were used to identify the vertical structure of the Triassic top unconformity and to conduct hydrocarbon accumulation analysis.

Core and petrophysical data

In this study, five wells that had been drilled and cored in the unconformity structure were selected for core observations, and 10 wells (72 samples in total) with porosity and permeability data within 50 m above and 50 m below the unconformity surface were selected to analyze the unconformity's vertical structure. The core observations indicate that the weathered clay layer in the structure of the clastic rock unconformity is mostly variegated mudstone and aluminaceous mudstone with the parent rock's texture. The structure has been completely destroyed, and pores and fractures are not developed. The core of the weathered leaching zone is loose, with a good permeability, reticulated fractures, and dissolved pores. Iron oxides and clay minerals fill the space along the crack walls in the form of a thin film (Chen et al., 2008; Zhao et al., 2009). In terms of the physical properties, the porosity and permeability of the weathered leaching zone are higher than those of the residual layer above the unconformity and the unweathered original rock below the unconformity. The porosity and permeability decrease sharply near the weathered clay layer (Zou et al., 2014).

Chemical weathering index

Among the five wells drilled near the Triassic top unconformity, the entire well section of well Y76 was cored and 19 samples were selected from 11.4 m above the unconformity to 46.3 m below the unconformity (depth range: 1238.6–1296.3 m). The lithology includes sandstone, mudstone, and argillaceous siltstone. The contents of the major elements were determined using a Q/SY DQ0338-2000 rock mineral inorganic element analyzer and an X-ray fluorescence spectrometry (S4 PIONEER X-ray fluorescence spectrometer). The test steps were as follows: (1) the analysis method and sample preparation method were selected, and the basic parameter method was used for testing. (2) The prepared sample was placed in a sample cup and then put into the sample exchanger, which was automatically fed into the sample room. The X-ray tube emitted primary X-rays to irradiate the sample and stimulate the emission of fluorescent X-rays of the element to be measured. (3) The fluorescent X-rays radiated by the sample were dispersed into isolated monochromatic analytical lines through spectroscopic crystals, the intensity of each spectral line was measured using the detector, and the element concentration was converted according to the selected analytical method to obtain the element content to be measured in the sample. Finally, the contents of seven major element oxides, including Al₂O₃, SiO₂, Fe₂O₃, CaO, MgO, Na₂O, and K₂O, were determined.

The weathering index can be calculated using the calculation formula for the constant elements and weathering index, and the theoretical limit values of the parameters of the unweathered and completely weathered rocks were determined for each weathering index (Table 1). The unconformity's structural layer can be quantitatively identified according to the theoretical limit values. In this study, four weathering indices that are sensitive to the identification of clastic unconformity structures, namely the Ruxton ratio (R), chemical index of alteration (CIA), plagioclase index of alteration (PIA), and iron aluminum weathering index (K), were selected (Ruxton, 1968; Zou et al., 2014).

Table 1.

Main chemical weathering index calculation formula and theoretical limit value*.

Weathering index	Calculation formula	Unweathered	Completely weathered	Data source
R	SiO₂/Al₂O₃	>4	<4	Ruxton (1968)
CIA	100×Al₂O₃/(Al₂O₃+ CaO + Na₂O + K₂O)	≤50	100
PIA	100 × (Al₂O₃-K₂O)/(Al₂O₃+ CaO + Na₂O-K₂O)	≤50	100
K	100×Al₂O₃+ Fe₂O₃)/(Na₂O + K₂O + CaO + MgO+SiO₂+ Al₂O₃+ Fe₂O₃)	<20	>30	Zou et al. (2014)

*In the formula, all oxides are mole ratios; MgO is the MgO content in silicate minerals.

CIA: chemical index of alteration; K: iron aluminum weathering index; PIA: plagioclase index of alteration; R: Ruxton ratio

Multivariate statistical method of conventional logging curve

In the logging identification of the unconformity structure, two multivariate statistical methods were used. The optimal segmentation method was used to determine the location of the unconformity surface. Principal component analysis (PCA) was used to identify the boundaries between the weathered clay layer, weathered leaching zone, and unweathered rock under the unconformity surface. The multivariate statistical analysis was completed using the open source software Jamovi 2.2.5.

Optimal segmentation method

There are clear differences in the sedimentary conditions of the upper and lower strata of the unconformity, resulting in abnormal responses and abrupt changes in the logging curves above and below the unconformity surface (Chen et al., 2015; Zhang et al., 2020). The optimal segmentation method was applied to the ordered data by regarding the top and bottom of the unconformity surface as different systems, and the sum of the squared deviations (S_n, n is the number of samples) was used as the index for dividing the unconformity surface. The S_n of the well logging curve values in the same system was kept as small as possible, while the sum of the squared deviations between the different systems was kept as large as possible. Based on this principle, the target interval was repeatedly divided into two sections using the dichotomy method, and the point with the smallest S_n was selected as the depth of the unconformity surface to ensure that in the upper and lower layers of the unconformity, the difference within the layers was the smallest and the difference between layers was the largest (Bao, 2005). The specific steps are as follows (Wang and Zhu, 2015).

Establishing a raw data matrix X = [x_ij] _n _× m

A total of m types of logging curves, such as the spontaneous potential (SP), natural gamma ray (GR), acoustic (AC), density (DEN), neutron (CNL), borehole diameter (CAL), and true formation resistivity (Rt), which have obvious response characteristics to unconformity structures, were selected as variables, and n orderly and equidistant samples near the unconformity surface were chosen to form a data matrix with m variables and n samples.

X = [x_{i j}]_{n \times m} = (\begin{matrix} x_{11} & x_{12} & \dots & x_{1 m} \\ x_{21} & x_{22} & \dots & x_{2 m} \\ ⋮ & ⋮ & \dots & ⋮ \\ x_{n 1} & x_{n 2} & \dots & x_{n m} \end{matrix}),

(1)

where element x_ij represents the observed value of the jth variable of the ith sample.

Standardizing the data

To eliminate the influence of the order of magnitude difference between the logging parameters on the calculation results, it was necessary to first normalize the data, transform equation (1) using the range normalization method, and obtain a new data matrix Z = [z_ij] _n _× m.

z_{i j} = \frac{(x_{i j} - min_{1 \leq i \leq n} x_{i j})}{max_{1 \leq i \leq n} x_{i j} - min_{1 \leq i \leq n} x_{i j}} (i = 1, 2, \dots, n; j = 1, 2, \dots, m;)

(2)

where z_ij is the new element obtained after the standardized processing of element x_ij, and its value is between 0 and 1.

Calculating the intrasegment variation matrix D = [d_ij] _n _× n

d_{i j} = \sum_{α = i}^{j} \sum_{β = 1}^{m} {[z_{α β} - {\bar{z}}_{β} (i, j)]}^{2} (i, j = 1, 2, \dots, n),

(3)

{\bar{z}}_{β} (i, j) = \frac{1}{j - i + 1} \sum_{α = i}^{j} z_{α β} (β = 1, 2, \dots, m) .

(4)

In equations (3) and (4), d_ij is variation in the ordered data segment and `z_β(i, j) the average value of column β in the ordered sequence segment of samples i to j.

Determining the depth of the unconformity surface

First, the entire target layer was divided into two layers, samples 2, 3,…, n−1 were taken as the dividing points, and the variation matrix D = [d_ij] _n _× n was calculated. Then, S_n(2; j) was calculated using equation (5).

S_{n} (2; j) = d_{1 j} + d_{j + 1, n} (j = 1, 2 \dots n - 1),

(5)

S_{n} (2; j^{*}) = \min_{1 \leq j \leq n - 1} S_{n} (2; j),

(6)

The minimum S_n(2; j*) was found, and the depth of sample j* corresponding to this value was defined as the depth of the unconformity surface.

Principal component analysis

PCA, a multivariate statistical method, of the logging data was conducted using the idea of dimension reduction to transform multiple logging curve variables with correlations into a few comprehensive indices (principal components) that were independent of each other and contained most of the original indices (more than 80–85%) (Zhao et al., 2007). The specific steps used to identify the unconformity's vertical structural layer were as follows (Wang and Zhu, 2015).

Establishing the raw data matrix X = [x_ij] _n _× m

The m types of conventional logging curves, such as the SP, GR, AC, and CNL, which can better reflect the lithology, skeleton structure, porosity, and permeability, were selected as variables. The n samples were collected at equal spacing from the lower part of the unconformity surface to form a data matrix with m variables and n samples (equation (1)).

Standardizing the data

The standard deviation standardization method was used to transform equation (1) and to obtain a new data matrix X’=[ $x_{i j}^{'}$ ] _n _× m.

x_{i j}^{'} = \frac{x_{i j} - {\bar{x}}_{j}}{\sqrt{\frac{1}{n} \sum_{i = 1}^{n} {(x_{i j} - {\bar{x}}_{j})}^{2}}} (i = 1, 2, \dots, n; j = 1, 2, \dots, m)

(7)

where x_ij is the observed value of the jth variable of the ith sample, x_j the average value of all of the observed values of the jth variable, and $x_{i j}^{'}$ the new element obtained after the standardization of element x_ij.

Establishing the correlation coefficient matrix R = [r_ij] _n _× m

r_{i j} = \frac{1}{n - 1} \sum_{k = 1}^{n} {x^{'}}_{i k} x_{j k}^{'},

(8)

R = [r_{i j}]_{n \times m} = (\begin{matrix} r_{11} & r_{12} & \dots & r_{1 m} \\ r_{21} & x_{22} & \dots & x_{2 m} \\ ⋮ & ⋮ & \dots & ⋮ \\ r_{n 1} & r_{n 2} & \dots & r_{n m} \end{matrix}) (i = 1, 2, \dots, n; j = 1, 2, \dots, m),

(9)

where r_ij represents the correlation coefficient of the jth variable of the ith sample.

Determining the principal components

The Jacobi method was used to calculate the eigenvalues λ_j (j = 1, 2, …, m) and the corresponding eigenvector u_j, variance contribution rate e_j, and cumulative variance contribution rate E_k (k = 1, 2, …, p, p < m) of matrix R. According to the principle of λ_k> 1 and E_k> 80% for determining p, the first p principal components (generally p = 2) and the eigenvector u_j were taken as the coefficient to write the expression.

P C_{k} = u_{1 k} x_{1} + u_{2 k} x_{2} + \dots + u_{m k} x_{m}

(10)

Establishing quantitative identification standards

The two principal components (PC₁ and PC₂) of multiple coring and testing wells that contained the unconformity were calculated and a cross plot was created. The statistical relationship chart between the unconformity's structural layer and the principal components was established, and the threshold values of principal components PC₁ and PC₂ for the different structural layers were determined. The principal component curves were calculated using equation (10) according to the selected logging curve variables, and the weathered clay layer, weathered leaching zone, and unweathered protolith were quantitatively divided according to the threshold values.

Results

Qualitative analysis of core and petrophysical data

The range of the unconformity's structural layers was roughly inferred from the changes in the core and petrophysical properties near the unconformity, but it was impossible to make a fine quantitative division. The observations of the core from well Y76 (Figure 3) revealed that at 1248.5 to 1250 m, the lithology is medium-fine sandstone without fractures or dissolved pores, with developed primary pores, and with oil-bearing oil spots or full oil immersion. This is the unweathered protolith. Below 1250 m, the mudstone is very broken and a network of weathering fractures has developed. These samples are mostly loose and needed to be stored in plastic bags. Dissolved pores are often present in the sandstone, and its petrophysical properties are significantly better than normal sedimentary sandstone. The lithology at 1250 to 1255 m is variegated mudstone, which is different from the other mudstone. The structure of the parent rock is incomplete; this is the weathered clay layer. The rock structure below 1295 m is complete, and the dissolved pores and fractures are not obvious. This is the unweathered protolith. A depth range of 1255–1295 m was determined to be the weathered leaching zone through a comparison of different cores.

Figure 3.

Lithology, petrophysical properties, and weathering characteristics of different structural layers of the Triassic top unconformity in well Y76.

It can be seen from the relationship between the petrophysical properties and the depths of the well points near the Triassic top unconformity (Figure 4) that the vertical porosity and permeability change significantly near the unconformity surface. In the upper part of the unconformity, the porosity and permeability gradually decrease with increasing distance from the unconformity surface. The petrophysical properties are good within approximately 0 to 20 m of the unconformity; this might be the residual layer. The porosity and permeability decrease sharply and reach their minimum values approximately 0 to 5 m below the unconformity; this might be the weathered clay layer. In the lower part of the unconformity surface, the porosity and permeability initially increase and then decrease with increasing distance from the unconformity surface, and the petrophysical properties are better in the range of approximately 0 to 40 m, which may be the weathered leaching zone.

Figure 4.

Relationship between petrophysical properties and depth of well points near the Triassic top unconformity in the Sanbian area. (a) Porosity changes with depth and (b) permeability changes with depth.

Quantitative analysis of chemical weathering index

The test results of the constant elements near the unconformity surface are shown in Table 2. Using the methods from Table 1, the variation curves of four weathering indices (R, CIA, PIA, and K) with depth were calculated from the contents of the constant elements (Figure 3). The four curves were within the range of 1238.6 to 1298.3 m. Although the lithology varies, the overall trend of variation can be clearly divided into four sections, and the weathering degree can be determined according to the weathering limit value in Table 1. Section ①, 1238.6 to 1250 m, R > 4, CIA < 50, PIA < 50, and K < 20, showing unweathered characteristics. Section ②, 1250 to 1255 m, R < 4, CIA close to 100, PIA close to 100, and K > 30, showing complete weathering characteristics. Section ③, 1255 to 1295 m, R < 4, 50 < CIA < 100, 50 < PIA < 100, and 20 < K < 30, showing partial weathering characteristics. Section ④, 1295 to 1298.3 m, R > 4, CIA < 50, PIA < 50, and K < 20, showing unweathered characteristics. Corresponding to the unconformity structure, the first section located on the unconformity surface, without weathering, is the residual layer. The second section has obvious weathering characteristics and is the weathered clay layer. The third section is partially weathered, and is the weathered leaching zone. The fourth section has no weathering characteristics and is the unweathered original rock.

Table 2.

Test and analysis of constant elements near the unconformity surface*.

Lithology	Sampling depth (m)	Distance from the unconformity surface (m)	Al₂O₃ (%)	SiO₂ (%)	Fe₂O₃ (%)	CaO (%)	MgO (%)	Na₂O (%)	K₂O (%)
Argillaceous siltstone	1238.60	11.40	10.59	44.46	4.42	11.45	6.19	0.69	2.27
Argillaceous siltstone	1242.00	8.01	16.63	57.95	2.49	4.70	2.13	1.48	2.12
Sandstone	1245.30	4.70	8.32	44.01	2.31	19.38	2.19	1.06	1.44
Sandstone	1249.80	0.20	14.23	63.96	3.19	3.64	1.68	1.57	1.90
Mudstone	1250.00	0	11.92	43.52	6.50	9.04	6.40	0.43	2.37
Mudstone	1252.23	−2.23	18.39	54.43	6.24	1.42	2.91	0.57	3.40
Mudstone	1253.70	−3.71	19.19	54.07	8.24	1.12	2.30	0.60	3.13
Mudstone	1255.00	−5.00	15.85	47.09	5.75	5.39	4.64	0.49	2.81
Mudstone	1258.00	−8.02	19.50	57.63	4.15	0.58	1.91	0.51	3.01
Mudstone	1260.50	−10.52	21.73	55.58	5.52	0.26	1.92	0.67	3.01
Mudstone	1263.23	−13.23	17.81	47.73	10.75	0.60	2.10	0.44	3.09
Mudstone	1266.00	−16.01	18.53	54.96	5.99	2.44	3.00	0.55	2.93
Mudstone	1268.50	−18.50	11.47	29.17	6.77	0.41	1.11	0.31	1.67
Mudstone	1274.70	−24.70	18.89	59.75	5.54	0.21	1.85	0.78	2.73
Mudstone	1276.40	−26.41	17.76	61.06	5.90	0.37	1.99	1.00	2.80
Mudstone	1279.40	−29.40	19.57	56.56	6.13	0.97	2.15	0.86	3.17
Mudstone	1281.46	−31.46	16.98	46.48	5.24	0.58	2.29	0.64	3.35
Argillaceous siltstone	1293.73	−43.73	11.25	44.46	4.21	12.36	6.54	0.75	2.38
Sandstone	1298.30	−48.30	8.63	44.01	2.52	19.21	2.36	1.08	1.44
Argillaceous siltstone	1238.60	11.40	10.59	44.46	4.42	11.45	6.19	0.69	2.27

* Constant elements were analyzed by Q/SY DQ0338-2000 inorganic element analysis method of rocks and minerals and X-ray fluorescence spectrometry.

Quantitative identification of unconformity surface and structure using conventional logging curves

Quantitative identification of unconformity surface position using logging curves

The above optimal segmentation method was used to quantitatively identify the unconformity surface in the exploration wells in the study area. Taking well Y76 as an example, the original data matrix, X = [x_ij] _n _× m (n = 140, m = 7), was established by selecting seven curves sensitive to the formation division, such as SP, GR, AC, DEN, CNL, CAL, and Rt. Using the steps corresponding to equations (2) to (6), Jamovi multivariate statistical analysis software was used to calculate the sum of the squared deviations S_n(2; j) (n is the number of samples, n = 140; j = 1, 2,…,n−1) and to form an optimal segmentation curve, the minimum point of which (j* = 1250 m) is the depth of the unconformity surface. The original geological stratification was located at 1251 m, which was 1 m different from the depth of the unconformity surface determined by the optimal segmentation method (Figure 5). According to the same method, the depth of the Triassic top unconformity surface was quantitatively identified in 40 typical wells containing different paleogeomorphology units and with different denudation degrees in the Sanbian area (Table 3). Compared with the original geological stratification, when ignoring the data with a difference of <0.5 m, the coincidence rate was 82.5% (33 wells), and there were seven wells that varied, accounting for 17.5%, with a difference range of 1.0 to 14 m.

Figure 5.

Quantitative identification of the vertical structure of the Triassic top unconformity in well Y76.

Table 3.

Comparison of geological stratification and optimal segmentation method identification results of the Triassic top unconformity surface.

Well number	Depth of unconformity surface (m)	Depth of geological stratification (m)	Difference value (m)	Well number	Depth of unconformity surface (m)	Depth of geological stratification (m)	Difference value (m)
1	1446.0	1446.0	0	21	1695.0	1695.0	0
2	2015.0	2015.0	0	22	1636.0	1636.0	0
3	1442.0	1442.0	0	23	732.7	732.7	0
4	1754.0	1754.0	0	24	1410.0	1410.0	0
5	1430.0	1430.0	0	25	1516.5	1516.1	0.4
6	1417.4	1417.0	0.4	26	1719.0	1719.0	0
7	1251.0	1250.0	1.0	27	1546.0	1546.0	0
8	1440.0	1440.0	0	28	1392.0	1390.0	2.0
9	1417.0	1417.0	0	29	1343.5	1343.7	−0.2
10	1224.0	1221.4	2.6	30	1183.0	1183.0	0
11	1411.0	1411.0	0	31	1658.0	1658.0	0
12	1633.0	1633.0	0	32	1499.0	1499.0	0
13	1553.0	1551.0	2.0	33	1888.0	1888.0	0
14	1713.0	1713.0	0	34	1625.0	1611.0	14.0
15	996.0	996.0	0	35	1616.4	1616.8	−0.4
16	1610.2	1604.0	6.2	36	1500.0	1500.0	0
17	1488.3	1488.0	0.3	37	1652.8	1652.6	0.2
18	1503.5	1495.0	8.5	38	1487.0	1487.0	0
19	1740.0	1740.0	0	39	1802.0	1802.0	0
20	1698.0	1698.0	0	40	1936.0	1936.0	0

Quantitative identification of unconformity structure using logging curves

Taking well Y76 as an example, it can be seen from the previous analysis that the weathered clay layer, weathered leaching zone, and unweathered protolith are located successively below the unconformity surface (Figure 4). The variation characteristics of the logging curves above and below the unconformity surface in the well show that the SP, GR, AC, DEN, and CNL curves have obvious responses to the unconformity structure, and they can be selected as five logging variables to establish the original data matrix X = [x_ij] _n _× m (n = 140, m = 5). Using the steps corresponding to equations (7) to (10), the eigenvalue λ_j (j = 1, 2,…,5), eigenvector u_j, and variance contribution ej of the correlation coefficient matrix R were calculated using Jamovi software (Table 4). The cumulative variance contribution rate E_j of PC₁ and PC₂ is 87.81%, and the eigenvalues are >1, which meets the principal component selection criteria. In other words, the original five logging variables can be replaced by the two variables PC₁ and PC₂, and the loss of data information is very small. The expression of the two principal components (equations (11) and (12)) was determined using equation (10):

P C_{1} = 0.43 \times G R + 0.42 \times S P + 0.75 \times A C - 0.26 \times C N L - 0.13 \times D E N,

(11)

P C_{2} = - 0.20 \times G R - 0.79 \times S P + 0.53 \times A C + 0.03 \times C N L - 0.23 \times D E N .

(12)

Table 4.

Eigenvalue, eigenvector, and variance contribution rate of correlation coefficient matrix of well Y76 logging data.

Principal components PC_j	Eigenvalues λ_j	Eigenvector u_j					Variance contribution rate e_j (%)	Cumulative variance contribution rate E_j (%)
Principal components PC_j	Eigenvalues λ_j	GR	SP	AC	CNL	DEN	Variance contribution rate e_j (%)	Cumulative variance contribution rate E_j (%)
PC₁	3.18	0.43	0.42	0.75	−0.26	−0.13	63.54	63.54
PC₂	1.21	−0.20	−0.79	0.53	0.03	−0.23	24.27	87.81
PC₃	0.36	0.52	−0.25	0.11	0.39	0.71	7.26	95.07
PC₄	0.15	0.53	−0.07	−0.21	0.5	−0.65	3.01	98.08
PC₅	0.10	−0.48	0.36	0.33	0.73	0.02	1.92	100.00

AC: acoustic; CNL: neutron; DEN: density; GR: natural gamma ray; SP: spontaneous potential.

The principal components of each sample were calculated to form principal component curves PC₁ and PC₂. It can be seen from Figure 5 that PC₁ is bounded by 250, and PC₂ is bounded by 90, which has an obvious response to the unconformity structure. The principal component curve range of the unconformity structure can be further summarized by combining the previous results of the core observations and weathering index analysis. (1) Above 1250 m and below 1295.9 m (the weathering index discrimination is 1295 m, and the difference between the weathering index and the core observation result is 0.9 m), the lithology is unweathered protolith, and the principal component curve ranges are PC₁≤ 250 and PC₂≥ 90. (2) The weathered clay layer is located at 1250 to 1255 m, where PC₁≥ 250 and PC₂≤ 90. (3) The weathered leaching zone is located between 1255 m and 1295.9 m. The overall curve range is PC₁≤ 250 and PC₂≤ 90, but the curve range is PC₁≥ 250 and PC₂ ≥ 90 at some depths (e.g., 1260 m).

What are the geological implications of principal component curves PC₁ and PC₂? The degree of weathering of the unconformity gradually decreases from top to bottom; that is, from the weathered clay layer to the weathered leaching zone and then to the unweathered protolith. The general trend is that the degree of clayization decreases and the degree of preservation of the protolith's structure increases. The variations in the principal component curve for well Y76 exhibit a downward trend for PC₁ and an upward trend for PC₂. This indicates that principal component PC₁ may be related to the degree of clayization, and is thus defined as the clayization factor, while PC₂ may be related to the preservation degree of the protolith's structure, and is thus defined as the protolith preservation factor.

Through single well analysis, PCA was conducted on 40 exploration wells in the study area. Five well cores containing the Triassic top unconformity structure were selected, and the data points (N = 946) of the unconformity's different structural layers were plotted on the same plot of PC₁ versus PC₂. The chart showing the statistical relationship between the Triassic top unconformity's structure and principal components PC₁ and PC₂ for the well logging data from the Sanbian area was established (Figure 6(a)).

Figure 6.

(a) Cross plot of the principal components of the Triassic top unconformity in the Sanbian area (data from five well cores). (b) Cross plot of the principal components of the Triassic top unconformity of well Y76.

The thresholds of principal components PC₁ and PC₂ were determined to be 250 and 90, respectively. According to the two threshold lines, the map can be divided into four regions: I, II, III, and IV. Among them, area I is the weathered clay layer area, in which PC₁ is the largest and PC₂ is the smallest, indicating the highest weathering degree. Area III is the unweathered protolith area, in which PC₁ is the smallest and PC₂ is the largest, that is, the opposite of area I, indicating that the weathering degree is the weakest. Areas II and IV are the weathered leaching zone. Most of the data points are distributed in area II, in which PC₁ and PC₂ are small. Fewer data points are distributed in area IV, in which PC₁ and PC₂ are large. The specific principal component division criteria for the unconformity's vertical structure are presented in Table 5.

Table 5.

Quantitative identification standard of the Triassic top unconformity vertical structure in the Sanbian area.

Unconformity structure	Distribution area	Principal component interval
Weathered clay layer	Ⅰ	PC₁ ≥ 250, PC₂ ≤ 90
Weathered leaching zone	Ⅱ, IV	PC₁ ≤ 250, PC₂ ≤ 90 or PC₁ ≥ 250, PC₂ ≥ 90
Unweathered protolith	Ⅲ	PC₁ ≤ 250, PC₂ ≥ 90

To further analyze the influence of the lithology on the principal component curve, the principal component curve for Y76 well was projected onto the plot of PC₁ versus PC₂ according to the different lithologies. It can be seen from Figure 6(b) that the data points with the same lithology plot in different areas. For example, the mudstones and fine sandstones in the weathered leaching zones and the unweathered protolith plot in different zones based on the principal component curves. It can be concluded that although the unconformity’s structural layers have the same or similar lithologies, principal component curves PC₁ and PC₂ can accurately reflect the characteristics of the formation that has been subjected to weathering and leaching, that is, they can visually, effectively, and quantitatively identify the unconformity's structure based on the logging data.

Discussion

Precision analysis of quantitative identification of the unconformity structure

Necessity of quantitative identification of the unconformity surface

The location of the unconformity surface is the pre-requisite for accurate identification of the unconformity's structure. It is generally believed that the unconformity surface is also the interface between the strata, which was determined in the early stratigraphic division and correlation. However, in many areas, it has been found that the geological stratification does not strictly correspond to the unconformity surface identified using the optimal segmentation method, with a deviation of 7.5% to 9.4% and difference range of 0 to 10 m (Chen et al., 2005; Zhang, 2008; Wang and Yang, 2010). According to the quantitative identification results of the Triassic top unconformity surface in 40 typical wells in the Sanbian area, the difference between the re-identified unconformity surface and the original geological stratification accounts for 17.5%, and the difference range is 1.0 to 14 m (Table 3). Compared with previous research results, the difference ratio of this study is slightly higher, primarily for two reasons. First, some of the wells in the study area were drilled earlier, and the geological stratification was mostly manually drawn, which can easily lead to errors. Second, previous scholars ignored the data with a difference of <2 m and only used the data with a difference of >2 m. However, the thickness of the weathered clay layer of an unconformity in a clastic basin is generally 0.5 to 20 m (Song et al., 2010; Wu et al., 2012), so a minimum difference of 2 m can result in missing the entire weathered clay layer and part of the weathered leaching zone. Therefore, in this study, only the differences below 0.5 m were ignored. This increased the proportion of difference values, but the results are more authentic and reliable. The 17.5% difference could not be ignored in this study, making it necessary to re-correct the depth of the unconformity interface.

The lithology influences the accuracy of the quantitative identification of the unconformity surface. The principle of the optimal segmentation method, which was used to determine the unconformity surface, is using repeated iterations to identify the position of the point with the smallest difference in the layers and the largest difference between layers on and below the unconformity surface, which is somewhat affected by the lithological changes. When the lithological change in the formation is serious, that is, much higher than that at the unconformity surface, the optimal segmentation point may reflect the location of the lithological change rather than the location of the unconformity surface. Chen et al. (2015) discussed this issue and concluded that first-level unconformities are largely not affected by the lithology, while second-level unconformities are notably affected by the lithology. The influence of the lithology can be weakened by the curve reconstruction; for example, the AG = AC/GR curve has been used to replace the AC or GR curve (Chen et al., 2015). There are two main reasons for the lack of lithological influence on the analysis in this study. First, the Triassic top unconformity in the study area is a first-level unconformity, and studies in several areas have shown that the optimal segmentation method has a good effect in the quantitative identification of first-level unconformity surfaces based on logging data (Zhang, 2008; Chen et al., 2010), so the influence of the lithology on the analysis can be ignored. Second, there is no other effective method of eliminating the influence of the lithology except for the curve reconstruction method, and the curve reconstruction method is not very clear in terms of its theoretical basis and geological significance; thus, it still requires further discussion before it can be applied.

Precision of the standard for quantitative identification of unconformity structures

PCA is not significantly affected by lithology in the identification of unconformity structures (Figure 6(b)), and it has a clear geological significance. However, it should be noted that the unconformity principal component plot and the quantitative identification standard of the structure are finally established based on the statistics of the data, and their accuracy mainly depends on the richness of the statistical samples. If the data permit, the more exploration well data are used to create the plot, the more reliable the standard for the quantitative identification of the unconformity structure will be. Previous scholars have used 5 to 7 coring wells in different areas to establish the principal component identification standard for an unconformity structure, and the threshold range was 60 to 65 for PC₁ and 30 to 40 for PC₂ (Zhao et al., 2007; Chen et al., 2010; Lu, 2018). In this study, the identification standard established based on the data from five coring wells was applied, and the thresholds were 250 for PC₁ and 90 for PC₂ (Table 5). Compared with previous studies, the number of samples used to establish the standard was similar, but the thresholds were quite different. The reason for this is that the unit of the acoustic curve (AC) was different. In previous studies, the unit of the AC was μs/m, while the AC unit in the study area was unified as μs/ft. The conversion factor between the two is about 3.28, and the thresholds are quite close after conversion. The standard for the identification of the unconformity's structure established in Table 5 can be considered to be the most accurate based on the current data for the study area, but as the number of coring wells that intersect the unconformity's structure increase, this standard will need to be further modified and improved.

Principal component analysis also has some limitations in the division of unconformity structures. First, the accuracy of the cross plot of the principal components of the unconformity depends on the number of core wells. If the number of core wells with diverse lithology is larger, the established unconformity structure identification standard will be more accurate. The identification standard established in Table 5 of this article can be regarded as the most accurate based on the current data in the study area, but with the increase in coring wells in the unconformity structure, the standard needs to be further modified and improved. Second, the calculation is relatively complex, which is more useful and more accurate in the selection of drilling targets. However, when the unconformity distribution is large and the amount of drilling is large, the workload is also large.

Unconformity characteristics of different paleogeomorphology units

The height, steepness, and gentle undulations of the paleotopography have important impacts on the development of unconformities (Zhao et al., 2009). In general, areas with high or steep paleotopography undergo significant physical weathering, and the erosion is relatively strong. The amount of fine debris formed by weathering is great in these areas, but it is difficult for this debris to remain in place, so the weathered clay layer is often missing. In addition, in mountain valleys, the erosion by flowing water is strong, and the weathered clay layer is largely undeveloped. In the relatively slow terrain, chemical weathering and biological weathering are the main types of weathering, and the fine weathered debris material is easily preserved (Li, 1994). The Triassic top paleogeomorphology in the study area can be divided into five units: river valleys, inter-river hills, slope mouth, slope, and highland (Figure 1(c)).

To clarify the development characteristics of the unconformity in the different paleogeomorphological units, quantitative identification of the unconformity structure of single wells and connected wells was carried out (Figure 7). For example, well A241 and well Y47 are located on the slope, both of which have a complete three-layer unconformity structure, including the residual layer (water-bearing sand body), weathered clay layer, and weathered leaching zone. However, the weathered leaching zone of well A241 is sandstone, which is a type of sandstone–claystone–sandstone combination, and can be referred to as the ADE type (Figure 8). The weathered leaching zone of well Y47 is a sand–mud interbed, a type of sandstone–claystone–sand mud interbed combination, and is of the ADG type. Well H6 is located in the river valley, lacks a weathered clay layer, and has only a two-layer structure. The thicker water-bearing sand body is in direct contact with the weathered leaching zone, and is of the AG type. The A319 well is located on the slope mouth and also has a three-layer structure, and is of the ADG type.

Figure 7.

Connected profile of the unconformity structure of an important exploration well (the profile location is shown in Figure 1(c)).

Figure 8.

Unconformity structure and genetic model of different paleogeomorphic units in the Triassic top unconformity in the Sanbian area (the genetic model was modified according to a previous study (Ding and Zhang, 2010)).

According to the above method, the unconformity structure of 40 key exploration wells (see Figure 1(c)) in the study area has been quantitatively identified. The results show that there are three genetic models of unconformity developed in five paleogeomorphic units at the top of the Triassic in the Sanbian area, which can be divided into two structural types, type I and type II (Figure 8). Each structural type can be divided into nine lithologic combinations:

In type I, the unconformity has a complete three-layer structure, and it is distributed in the slope mouth and slope. According to the different lithological assemblages, this type can be divided into nine subtypes (defined in Figure 8): ADE, BDE, CDE, ADF, ADG, BDF, BDG, CDF, and CDG.

In type II, the unconformity only has a two-layer structure, and it generally lacks the weathered clay layer. It is mainly composed of the residual layer and the weathered leaching zone. Type II is distributed in the highlands, river valleys, and inter-river hill. According to the different lithological assemblages, type II can be divided into nine subtypes (defined in Figure 8): AE, AF, AG, BE, BF, BG, CE, CF, and CG.

Control of the Triassic top unconformity on the formation of its upper and lower reservoirs

In the unconformity's structure, the upper residual layer and the lower weathered crust (the weathered clay layer and weathered leaching zone) pass through six strata vertically. Among them, the residual layer includes two layers of the Jurassic Fuxian Formation and the Yan 10 member, and the weathered crust consists of four layers: the Chang 23, Chang 22, Chang 21, and Chang 1 members of the Triassic system (Figure 9). After dissecting 32 typical Mesozoic reservoirs and arranging them from left to right in order of increasing altitude (i.e. in the order of river valley–slope mouth–slope–highland), it was found that, in addition to serving as an important oil and gas-bearing bed (referred to as OB), the unconformity plays an important role in controlling the distribution of the reservoirs in its upper and lower parts, which is mainly reflected in the following aspects.

Figure 9.

Structure and reservoir distribution of the Triassic top unconformity in the Sanbian area (the location of the well is shown in Figure 1).

(1) Macroscopically, the unconformity and its upper and lower strata form three OBs: OB1 composed of the Yan 9 and Yan 10 members in the upper part of the unconformity, OB2 composed of the unconformity's structural layers, and OB3 composed of the unweathered protolith in the lower unconformity. The three OBs exhibit a competitive relationship, and the oil exhibits a complementary relationship (Figure 9). From bottom to top, when the oil reservoirs in OB3 are relatively well developed, the oil reservoirs in OB2 and OB1 are not developed or are poorly developed, such as A145 and A187, with a total of eight oil reservoirs. When the reservoirs in OB2 are developed, the reservoirs in OB3 and OB1 are not developed or are poorly developed, such as A106 and A185, with a total of 10 oil reservoirs. When the reservoirs in OB1 are developed, the reservoirs in OB2 and OB3 are not developed or are poorly developed, such as Y19 and Y57, with a total of eight oil reservoirs.

(2) The reservoirs in the Chang 1 and Chang 2 members in the denudation area of the Chang 1 member are evenly distributed in the weathered leaching zone in the lower part of the unconformity surface, which has a good lateral connectivity and can be used as an important lateral migration channel and reservoir. The water-bearing sand bodies in the residual layer only developed in the ancient channel, with poor lateral connectivity and a low oil content.

(3) The weathered clay layer has an important vertical sealing effect on the formation of the oil reservoir in the unconformity's structure. Weathered clay layers are developed in the upper part of almost all of the weathered leaching zone oil reservoirs. Vertical leakage occurs in areas where no weathered clay layer is developed, and the oil and gas are adjusted above the unconformity surface, such as in well L48 in the river valley unit and in well D26 in the highland unit.

Hydrocarbon migration and accumulation model of the Triassic top unconformity

The source rocks of the Mesozoic oil and gas in the study area are basically the Chang 7 member, and they migrated to the vicinity of the Triassic top unconformity surface through fractures or fracture-sand body channels in the vertical direction. Under the influence of the weathered clay layers, significantly different hydrocarbon migration and accumulation modes formed above and below the unconformity surface.

(1) A hydrocarbon migration and accumulation model of the weathered crust (Chang 1–Chang 2 member). The oil and gas vertically migrated from the lower Chang 7 source rock can be macroscopically divided into two parts. One part of the oil and gas migrated laterally from the river valley to the highland along the unconformity's weathered leaching zone, which is composed of the Chang 1 and/or Chang 2 member, and this part of the oil and gas was vertically sealed by the weathered clay layers at the slope mouth and slope area to form an unconformity shielding reservoir. When the other part of the oil and gas migrated to the river valley, due to the lack of a weathered clay layer, the weathered leaching zone as in direct contact with the upper ancient channel sand body of the Fuxian Formation and/or the Yan 10 member, forming a vertical leakage skylight, so the oil and gas passed through the unconformity surface and entered the upper residual layer (Figure 10).

Figure 10.

Hydrocarbon migration and accumulation model of the Triassic top unconformity in the Sanbian area (modified from Fu et al., 2013).

(2) A hydrocarbon migration and accumulation model of the residual layer (Fuxian Formation–Yan 10 member). After vertical adjustment in the valley, the oil and gas migrated laterally toward both sides of the slope mouth. The sand body channel of the Fuxian Formation is the main carrier layer, and it lacks effective vertical sealing conditions, resulting in poor oil and gas accumulation. The oil and gas were further adjusted to the Yan 10 and Yan 9 members and were blocked by the regional caprock formed by the Yan 8 member. Then, they converged to form reservoirs in the high parts of the local structures. Influenced by the range of source rocks, the oil and gas are mainly enriched in the mouth of the slope around the river valley, and in some areas, the oil and gas migrated to the slopes to form reservoirs (Figure 10).

Conclusions

Through quantitative identification of the vertical structure of the Triassic top unconformity in the Sanbian area, it was revealed that the unconformity is of great significance to the Mesozoic hydrocarbon migration and accumulation in the study area. Five detailed conclusions were drawn.

(1) Seven logging curves, including SP, GR, CAL, AC, DEN, CNL, and Rt curves, were selected, and the location of the unconformity surface can be quickly determined using the optimal segmentation method, which corrected the 17.5% error of the geological stratification as unconformity interface in the study area.

(2) Based on core observations, petrophysical properties, and a weathering index analysis of five core wells, five logging curves (GR, SP, AC, CNL, and DEN) were selected to establish a quantitative identification of the unconformity's vertical structure through PCA. The standards were as follows: for the weathered clay layer, PC1 ≥ 250 and PC2 ≤ 90; for the weathered leaching zone, PC1 ≤ 250 and PC2 ≤ 90 or PC1 ≥ 250 and PC2 ≥ 90; and for the unweathered protolith, PC1 ≤ 250 and PC2 ≥ 90. According to this standard, the unconformity's vertical structure can be quantitatively identified in the exploratory wells without coring data in the study area.

(3) There are two types of unconformity structures in the five Triassic top paleogeomorphological units in the study area. Among them, type I is an unconformity with a complete three-layer structure (residual layer, weathered clay layer, and weathered leaching zone) and type II is an unconformity with a two-layer structure, that is, without a weathered clay layer. The slope mouth and slope developed a type I unconformity, while the highland, river valley, and inter-river hill developed a type II unconformity.

(4) The unconformity's structural layer can be regarded as an independent oil and gas-bearing bed (OB) that has a competitive relationship with the upper Yan 9 to Yan 10 members and the lower unweathered rocks, while hydrocarbon exhibits a complementary relationship with the three oil and gas-bearing beds; that is, when the unconformity is rich in oil, the upper and lower oil and gas-bearing beds are generally poor in oil, and vice versa.

(5) There were two modes of hydrocarbon migration and accumulation in the unconformity's structure. First, in the weathered crust under the unconformity surface (Chang 1–Chang 2), the hydrocarbons migrated to the slope mouth and the slope unit was blocked by the weathered clay layer, so the hydrocarbons accumulated and leaked vertically into the shallow layer in the river valley. Second, in the residual layer (Fuxian Formation to Yan 10) on the unconformity surface, the channel sand body of the Fuxian Formation served as the carrier layer to adjust the oil and gas to the local structural high position in the slope mouth area of the Yan 10 to Yan 9 members, where it accumulated and formed reservoirs.

Footnotes

Acknowledgements

We thank Research Institute of Exploration and Development of Changqing Oilfield Company, PetroChina for providing basic data. We also thank the editors and commentators for their suggestions and comments.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Natural Science Foundation of China (No.: 41602164), and the scientific research fund of Guangdong University of Petrochemical Technology (No.: 2018rc02) and Guangdong Provincial College Youth Innovation Talent Program (No.: 2018KQNCX160).

ORCID iD

Tongwen Sun

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