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Analysis of pore throat characteristics of tight sandstone reservoirs

  • Xinli Zhao ORCID logo , Zhengming Yang , Xuewei Liu EMAIL logo , Zhiyuan Wang and Yutian Luo
Published/Copyright: October 12, 2020
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Open Geosciences
From the journal Open Geosciences Volume 12 Issue 1

Abstract

The characterization of pore throat structure in tight reservoirs is the basis for the effective development of tight oil. In order to effectively characterize the pore -throat structure of tight sandstone in E Basin, China, this study used high-pressure mercury intrusion (HPMI) testing technology and thin section (TS) technology to jointly explore the characteristics of tight oil pore throat structure. The results of the TS test show that there are many types of pores in the tight sandstone, mainly the primary intergranular pores, dissolved pores, and microfractures. Based on the pore throat parameters obtained by HPMI experiments, the pore throat radius of tight sandstone is between 0.0035 and 2.6158 µm. There are two peaks in the pore throat distribution curve, indicating that the tight sandstone contains at least two types of pores. This is consistent with the results of the TS experiments. In addition, based on the fractal theory and obtained capillary pressure curve by HPMI experiments, the fractal characteristics of tight sandstone pore throat are quantitatively characterized. The results show that the tight sandstones in E Basin have piecewise fractal (multifractal) features. The segmentation fractal feature occurs at a pore throat radius of approximately 0.06 µm. Therefore, according to the fractal characteristics, the tight sandstone pore throat of the study block is divided into macropores (pore throat radius > 0.06 µm) and micropores (pore throat radius < 0.06 µm). The fractal dimension DL of the macropores is larger than the fractal dimension DS of the micropores, indicating that the surface of the macropores is rough and the pores are irregular. This study cannot only provide certain support for characterizing the size of tight oil pore throat, but also plays an inspiring role in understanding the tight pore structure of tight sandstone.

Keywords: tight sandstone; high-pressure mercury intrusion; thin section; pore throat structure; fractal dimension; E Basin

1 Introduction

As an unconventional oil and gas resource, tight oil and gas has received more and more interest in researchers [1,2]. In China, tight sandstones are defined as reservoirs with the porosity of <10%, and gas permeability <1 × 10−3 µm2 [3,4]. The tight reservoir has extremely low porosity and permeability, so it has no natural capacity. Generally, the development of tight oil requires volumetric fracturing to obtain an industrial oil stream [5]. In addition, the pore throat structure is a significant parameter affecting the seepage of tight oil during the development [6,7,8,9]. However, characterizing the multiscale (nano-millimeter) pore throat structure distribution system of tight sandstones is a difficult research point.

For now, the techniques for the characterization of tight oil pore throat structure mainly include rate-controlled mercury intrusion (RCMI), high-pressure mercury intrusion (HPMI), low-temperature nitrogen adsorption (LTNA), scanning electron microscope (SEM), thin section (TS), X-ray computer tomography (CT), and nuclear magnetic resonance (NMR) techniques [10,11,12,13,14,15,16,17,18,19,20]. However, various technologies just mentioned have their respective advantages and disadvantages in practical applications [21]. For example, RCMI technology can obtain pores and throats in tight sandstones according to its testing principles, but it can only test pore throats larger than 0.1 µm [22]. The LTNA technology can only test the pores of less than 100 nm in tight sandstone and its accuracy in calculating the pore radius depends on the choice of the calculation model [23,24,25]. In addition, NMR technology can perform nondestructive testing of the pore throat radius distribution characteristics of the porous media, but the conversion of the T2 spectrum (transverse relaxation time) into the pore throat radius distribution requires a combination of other testing techniques (such as RCMI) [26]. SEM, TS, and CT techniques can qualitatively and intuitively observe information such as pore throat size, connectivity, and pore throat type in rocks [27,28,29]. In addition, SEM technology can also obtain information on the composition of minerals in rocks, which is widely used to analyze the petrological characteristics of tight sandstones. Therefore, in order to accurately characterize the distribution characteristics of multiscale pore throat structures in tight sandstones, a technique capable of testing the full range should be proposed. The HPMI is carried out by injecting a nonwetting phase (mercury) into a tight sandstone core by high pressure to obtain a distribution of pore throat radius in the core. The test range is from nanometer to micrometer, which can describe the distribution characteristics of tight sandstone pore throat radius. Additionally, this technology has been widely used in the study of rock pore throat structures and numerous successful applications of HPMI technology have already shown its efficiency for pore throat characterization [30,31,32].

Fractal geometry is an effective means of describing irregular objects in nature [33]. Since its development and promotion by Mandelbrot and Wheeler in 1983, many scholars have successfully applied it to the petroleum industry to study the fractal features of complex and irregular pore throat structures in porous media [34,35,36]. In addition, with the exploration and development of tight oil, many scholars use fractal theory to quantitatively characterize the tight sandstone nanoscale pore throat network system [37,38]. It is found that the complex pore throat structure of tight sandstone has fractal characteristics, and its fractal dimension is large, which has the characteristics of segmentation and fractal [39,40]. It indicates that the tight sandstone pore throat surface is irregular, rough, and heterogeneous. Moreover, the classification of pore throat size for tight sandstones is also a part of the exploration phase. Although some scholars and institutions have proposed some classification methods for pore throat size, the tight sandstones for specific blocks need to be classified according to their own characteristics. For example, in the pore throat size classification method proposed by the International Union of Pure and Applied Chemistry, micropores are less than 2 nm in width, mesopores in the range of 2 to 50 nm in width, and width of the macropores is greater than 50 nm [41]. This classification method is widely used in the pore throat radius distribution of shale. Nevertheless, in the study of tight oil, this classification method almost divides all pores into large pores. This is definitely not accurate enough in the petroleum industry [42]. Additionally, in terms of rock pore size classification, Pittman proposed an empirical formula for predicting the pore distribution curve based on the experimental data of 202 core samples [43]. Loucks et al. extended Choquette and Pray’s pore size classification for carbonates and proposed a new pore size classification scheme. In this scheme, nanopores range from 1 nm to 1 µm, micropores range from 1 to 62.5 µm, and mesopores from 62.5 µm to 4 mm [44]. However, for tight oil pore throat radius is generally less than 1 µm, this method has certain limitations in the classification of pore throats of tight sandstone. As the tight sandstone has the characteristics of segmentation and fractal, according to the critical point of the segment the pore throat size can be classified.

In this study, HPMI and TS experiments were carried out using the tight oil cores of the drilled E Basin. The TS can visually observe the pore throat type in the core and characterize the core pore throat structure qualitatively. In addition, based on the HPMI experiment, this paper used the fractal theory to quantitatively characterize the pore throat structure of tight sandstone.

2 Samples

The core samples of tight sandstone selected in this study are taken from Honghe Oilfield and Weibei Oilfield in E Basin, China. The tight sandstones in the E Basin mainly include lithic arkose sandstones and feldspathic litharenite sandstones, according to Folks classification (see Figure 1). And, their relative content accounts for about 50%. Detailed information of 12 core samples is shown in Table 1. The permeability of the core sample is between 0.202 × 10−3 µm2 and 1.785 × 10−3 µm2 with an average of 0.558 × 10−3 µm2. And, the core samples have a porosity between 7.6% and 12.9% with an average of 10.2%. Therefore, according to Chinese petroleum industry standards, these cores are typical tight sandstones.

Figure 1 Triangular diagram of rock composition of tight sandstone reservoir in E Basin.
Figure 1

Triangular diagram of rock composition of tight sandstone reservoir in E Basin.

Table 1

Information of experimental core samples

SampleWellDepth (m)SubsectionPorosity (%)Perm (10−3 µm2)
WB49-66WB49569.81Weibei11.20.216
WB49-80WB49569.99Weibei12.00.393
WB14-59WB14570.16Weibei11.20.497
WB14-13WB14570.38Weibei12.10.399
WB49-53WB49570.84Weibei10.51.785
WB49-72WB49571.02Weibei9.10.202
HH153-10HH1532097.48Honghe8.30.223
HH153-61HH1532097.90Honghe10.61.04
HH153-66HH1532098.26Honghe9.80.769
HH153-80HH1532098.76Honghe7.60.341
HH153-91HH1532099.40Honghe9.50.530
HH153-100HH1532100.04Honghe8.90.295

3 Test and calculation method

3.1 HPMI and TS

The HPMI is based on a capillary beam model and assumes that the porous medium consists of capillary bundles of different diameters. The main measured value of the HPMI test is the mercury inlet pressure (corresponding to the throat radius) and mercury saturation (corresponding to pore throat volume). The HPMI equipment, named AutoPore IV 9520, was used to measure pore throat size and the maximum mercury pressure can reach about 206 MPa, corresponding to a pore throat radius of 3.5 nm. After the experiment reached the highest mercury inlet pressure, the pressure gradually decreased and mercury withdrew the core sample. In the HPMI experiment, the mercury injection and withdrawal capillary pressure curves were obtained and the pore throat characteristics of the tight sandstone were analyzed based on this. In addition, in this experiment, the temperature in the laboratory was 21°C and the humidity was 60%. At the same time, the capillary pressure curve can characterize the pore throat structure feature, because the capillary pressure is mainly controlled by pore throat network sorting and pore throat size. Through the relationship between capillary pressure (Pc) and pore throat radius (r), the curve of pore throat radius was obtained to assess the pore throat structure of the tight sandstone. Its calculation formula is as follows [45]:

(1)Pc=2σcosθr

where Pc is the capillary pressure in MPa, σ is the surface tension of air/mercury in N/m, θ is the contact angle in °, and r is the pore throat radius in µm. In addition, the surface tension of air/mercury is 485 mN/m and the contact angle is 140°.

In the TS method, the colored (red or blue) liquid glue is injected into the pores of rock under vacuum or pressure and ground it into thin slices after solidification by liquid gel. It is easy to identify under the microscope when the pores in the rock are filled with nonferrous glue. The information of pore distribution, type, development degree, and geometric shape can be observed directly in the core slice. In this study, the LEICA DMRXHC multifunctional polarizing microscope was used in the experiment of TS, and the information of pore type was observed.

3.2 Fractal dimension calculation

Fractal theory has been widely used in petroleum engineering since its establishment in the mid-1970s. It is studied in a disorderly and self-similar system that is widespread in nature. As a porous medium, rock’s pore throat system has self-similar properties. Li derived the calculation formula of fractal dimension based on the capillary model and studied the rock heterogeneity [46]. Wang et al. believe that different pore distribution characteristics of tight sandstones have different calculation methods of fractal dimension [47]. The previous studies have found that there is a relationship between pore volume, pore radius, and fractal dimension as described as follows:

(2)V∝r3−D

where V is the rock pore volume, m3; r is the pore radius, m; and D is the fractal dimension.

Deriving the derivative of equation (2), the following is obtained:

(3)dVdr∝r2−D

By integrating equation (3), an expression for the cumulative pore volume (V(>r)) with a pore radius greater than r is obtained:

(4)V(>r)=∫rrmaxαr2−Ddr=β(rmax3−D−r3−D)

where rmax is the maximum pore radius, m; α and β are the proportional constants, β=α/(3−D).

If the maximum pore radius and the minimum pore radius in the pore are known, the pore volume is calculated as follows:

(5)V=βrmax3−D−rmin3−D

where rmin is the minimum pore radius, m.

The cumulative volume fraction (S) can be expressed as follows:

(6)S=V(>r)V=rmax3−D−r3−Drmax3−D−rmin3−D

The minimum pore radius in tight sandstone is much smaller than the maximum pore radius, i.e., rmin≪rmax. Therefore, S can be reduced to the following formula:

(7)S=1rrmax3−D

Assuming that the contact angle is not affected by the pore throat size, then the fractal formula of pore throat radius distribution can be obtained.

(8)S=1−PcPmin3−D

where s is the volume of mercury entering the pores in the HPMI experiment, %; Pc is the capillary pressure, MPa; and Pmin is the capillary pressure corresponding to the maximum pore throat radius rmax (i.e., capillary pressure of entrance).

Taking the logarithm of the two sides of equation (8) can get the following formula:

(9)log(1−s)=(D−3)logPc−(D−3)logPmin

In the HPMI test, 1-s represents the saturation of the wetted phase, which can be expressed in Sw. Therefore, equation (9) can be expressed as follows:

(10)logSw=(D−3)logPc−(D−3)logPmin

Based on the HPMI experiment, the fractal dimension of the rock pore throat network system can be calculated according to equations (9) and (10) and the microstructure characteristics of the porous medium also can be described.

4 Results

4.1 Petrological characteristics and pore throat types

There are various types of cuttings, mainly metamorphic rocks and sedimentary rocks, including igneous rocks and mica, and the soft rock cuttings are pseudo-matrix. Interstitials include heterobases and types of cement with a low volume fraction, generally less than 10%, with an average of 8.6%. The heterogeneous base is mainly muddy (Figure 2b and d). Some of the muddy rock fragments are rich in organic matter and the compacted deformation is pseudo-matrix. The cement is made of mainly calcite and dolomite and contains a small amount of quartz, feldspar, pyrite, and kaolinite. Quartz is mainly single-crystal quartz, and most of them are subribbed. The types of pores include primary pores, secondary pores, heterobasic pores, and microfractures. The pores are mainly triangular and multilateral intergranular pores, and some intergranular pores are enlarged by dissolution. Among them, the intergranular filling is mixed with chlorite, calcite, dolomite, and a small amount of heavy oil (Figure 2c). At the same time, it was found that there were under-developed pores and uneven distribution, which were isolated fine intergranular pores. Its pore size is 0.05–0.20 mm and the maximum is 0.38 mm (Figure 2l). Followed by feldspar and mudstone debris (Figure 2h), there are mold pores also (Figure 2g), the general diameter of 0.05–0.12 mm and the maximum of 0.18 mm. The characteristics of the pore throat are mainly point-shaped pore throat, a small number of thin tubular and flaky. The other type is feldspar formed by dissolution, dissolved pores in rock fragments and a small number of miscellaneous pores. The pore coordination number is 0–2. There is a point-like pore throat in the sandstone of the study block, and the local dissolution crack is 0.025–0.75 mm (Figure 2j). Although the development of fractures has little effect on increasing reservoir space, it can significantly improve reservoir seepage capacity [48,49]. In addition, the particle size is mainly in fine sand–fine sand (Figure 2a–e) and medium sand–fine sand grade (Figure 2f–l). In this study, the rock sorting performance of the tight reservoir in the block is moderate–good. The rounding is usually shown as an angular–secondary angular shape, and the particles are mainly dominated by line contact. The types of cementation are film – pore and film – embedded crystal type.

Figure 2 Tight sandstone TS analysis of the type of pore throat. (a) Intergranular pore, moldic pore (WB49-66, 569.81 m); (b) dissolved pore of mudstone (WB49-66, 569.81 m); (c) feldspar dissolved pore (WB49-66, 569.81 m); (d) kaolinite dissolved pore, calcite, heterogroup (WB49-80, 569.99 m); (e) feldspar dissolved pore, intergranular pore (WB14-59, 570.16 m); (f) quartz overgrowth (HH153-100, 2100.04 m); (g) moldic pore (HH153-100, 2100.04 m); (h) cementation metasomatism of calcite, intragranular dissolved pore (HH153-100, 2100.04 m); (i) flake debris (HH153-100, 2100.04 m); (j) solution microfracture (HH153-100, 2100.04 m); (k) calcite (HH153-100, 2100.04 m); (l) intergranular pore (HH153-100, 2100.04 m). IP, intergranular pore; FDP, feldspar dissolved pore; DP, dissolved pore; FD, flake debris; MF, microfracture.
Figure 2

Tight sandstone TS analysis of the type of pore throat. (a) Intergranular pore, moldic pore (WB49-66, 569.81 m); (b) dissolved pore of mudstone (WB49-66, 569.81 m); (c) feldspar dissolved pore (WB49-66, 569.81 m); (d) kaolinite dissolved pore, calcite, heterogroup (WB49-80, 569.99 m); (e) feldspar dissolved pore, intergranular pore (WB14-59, 570.16 m); (f) quartz overgrowth (HH153-100, 2100.04 m); (g) moldic pore (HH153-100, 2100.04 m); (h) cementation metasomatism of calcite, intragranular dissolved pore (HH153-100, 2100.04 m); (i) flake debris (HH153-100, 2100.04 m); (j) solution microfracture (HH153-100, 2100.04 m); (k) calcite (HH153-100, 2100.04 m); (l) intergranular pore (HH153-100, 2100.04 m). IP, intergranular pore; FDP, feldspar dissolved pore; DP, dissolved pore; FD, flake debris; MF, microfracture.

4.2 Distribution characteristics of pore throat

The distribution curve of the pore throat radius was obtained by HPMI experiment (Figure 3). The pore throat radius distribution curve shows multiple peaks. It suggests that there are multiple kinds of pore types in the tight sandstone, which is consistent with the results obtained by the TS experiment (Figure 2). In addition, the existence of multiple peaks in the pore throat distribution curve suggests that the tight sandstone in the target reservoir is highly heterogeneous. In Figure 3a, the first peak is between 0.0035 and 0.01 µm and the second peak is between 0.01 and 2.615 µm. However, in Figure 3b, the first peak is between 0.0035 and 0.0408 µm and the second peak is between 0.0408 and 2.615 µm. Besides, with the increase of permeability, the pore throat distribution curve shows a trend of gradually moving to the right. The pore throat radius of the tight sandstone in the study block is between 0.0035 and 2.6158 µm, and the pore throat is well developed below 1 µm. From Figure 4, the contribution of permeability in tight sandstone that is mainly pore throat with a radius between 0.1 and 1 µm can be acquired. And with the increase of permeability, the larger pore throat radius has a greater impact on the permeability contribution. The characteristics of the tight sandstone capillary pressure curve are shown in Figure 5. The capillary pressure curve of the sample in the study area is slightly skewed, which shows that the pore throat is very small. Table 2 shows the relevant parameters of tight sandstone obtained by HPMI experiment. It is noteworthy that the threshold pressure (Pt) of the tight sandstone in the study block is mainly distributed between 0.45 and 1.47 MPa, with an average of 0.78 MPa. It has a certain negative correlation with the permeability, that is, the larger the permeability, the smaller the threshold pressure (Figure 6a). At the same time, there is a good positive correlation between the median radius (ra) and the permeability (Figure 6b). This shows that the median radius has a certain degree of influence on the permeability. In addition, the tight sandstone samples in the study block have a relatively high maximum mercury saturation, which is mainly distributed between 79% and 99%. However, the mercury withdraw efficiency (Sw) is relatively low, mainly distributed in 30% to 50%, and a large amount of residual mercury saturation remains in the pores. The previous studies have suggested that this is due to the complex pore structure of the low-permeability sandstone reservoir, and the difference in pore and throat distribution. The retained mercury in a large number of pores is caused by the shielding effect of small pores [50].

Figure 3 Pore throat radius distribution curve. (a) Honghe Oilfield; (b) Weibei Oilfield.
Figure 3

Pore throat radius distribution curve. (a) Honghe Oilfield; (b) Weibei Oilfield.

Figure 4 Permeability contribution distribution curve. (a) Weibei Oilfield; (b) Honghe Oilfield.
Figure 4

Permeability contribution distribution curve. (a) Weibei Oilfield; (b) Honghe Oilfield.

Figure 5 Mercury intrusion/extrusion curves of target reservoir in the E Basin. (a) Weibei Oilfield; (b) Honghe Oilfield.
Figure 5

Mercury intrusion/extrusion curves of target reservoir in the E Basin. (a) Weibei Oilfield; (b) Honghe Oilfield.

Table 2

HPMI test results

SampleφKXPSKCCCSSmaxPtraSw
WB49-6611.20.21612.940.030.151.8898.981.470.0649.27
WB49-8012.00.39311.691.180.192.2894.240.450.1432.52
WB14-5911.20.4979.491.660.282.7079.740.750.1135.96
WB14-1312.10.39910.091.720.262.6082.650.730.1136.56
WB49-5310.51.78511.450.490.192.2299.680.470.3040.89
WB49-729.10.20212.651.360.151.9295.351.210.0831.37
HH153-108.30.22312.500.910.172.0696.400.740.0849.48
HH153-6110.61.0411.710.650.202.3896.640.470.1239.43
HH153-669.80.76911.161.380.212.3791.820.450.1243.65
HH153-807.60.34112.340.910.192.3195.250.750.0747.11
HH153-919.50.53011.950.810.192.2496.800.460.1340.19
HH153-1008.90.29512.670.200.141.7999.511.460.1243.54

φ, porosity, %; K, permeability, 10−3 µm2; XP, mean value coefficient; SK, skewness coefficient; CS, sorting coefficient; CC, variable coefficient; Smax, maximum mercury saturation, %; Pt, threshold pressure, MPa; ra, median radius, µm; Sw, mercury withdrawal efficiency, %

Figure 6 Relationship between permeability and threshold pressure and median radius. (a) the relationship curve between permeability and pt; (b) the relationship curve between permeability and ra.
Figure 6

Relationship between permeability and threshold pressure and median radius. (a) the relationship curve between permeability and pt; (b) the relationship curve between permeability and ra.

5 Discussions

5.1 Fractal characteristics

The fractal theory is used to study the irregular elements with complex structures. Generally, fractal dimensions are used in this method to characterize object complexity. Based on the fractal dimension calculated by equations (8) and (9), the D is closer to 2, the simpler the pore throat structure, the more regular the pore throat shape. In addition, when D is closer to 3, it suggests that the more complicated the pore throat structure, the more irregular the shape. At the same time, according to the fractal theory, the fractal of pore throat structure can be divided into integral fractal (single fractal) and piecewise fractal (multifractal). The tight sandstone of this study block is characterized by multifractal, which means that there are differences in the structure of the large and small pore throats, and the fractal dimension is quite different. The tight sandstone pore throat of the E Basin has a good feature and the characteristics of segmentation fractals appear (R2 > 0.9, Figure 7). Combined with the double-logarithmic curve of capillary pressure and mercury saturation obtained from the HPMI test of these sandstone cores, the curve shows a turning point at the pore throat radius of about 0.0602 µm, which is divided into two regions, indicating that the pore throat has two different scales. According to the distribution characteristics of the tight pores of the study block, the pores of these two scales can be divided into macropores (pore throat radius > 0.0602 µm) and micropores (pore throat radius < 0.0602 µm). The fractal dimension of the macropores (DL) of the tight sandstone in the target oilfield is between 2.5609 and 2.7364, with an average of 2.6696 (Table 3). However, the fractal dimension of the micropores (DS) is between 2.0411 and 2.5526, with an average of 2.3256. Therefore, the fractal dimension of the large pore throat in the tight sandstone is larger than the fractal dimension of the micropore throat. This indicates that the structure of the micropore throat in the tight sandstone is relatively simple and the surface is relatively regular. The relative content of macropores and micropores in tight sandstone cores also can be derived. Among them, the proportion of macropores is 50.12 ∼ 82.10%, with an average of 64.34%. The proportion of micropores is 17.90 ∼ 49.88%, with an average of 35.66%. From Figure 8, as the permeability (Figure 8a) and porosity (Figure 8b) increase, the content of macropores in the core tends to increase. However, the proportion of micropores in the core shows a decreasing trend. In addition, the SW obtained by HPMI test is a key parameter reflecting the ultimate oil recovery of oil and gas. SW is mainly affected by the structure of the pore throat, so it can be used to characterize the pore throat structure of tight sandstone reservoirs. In tight sandstone reservoirs of E Basin, the SW gradually decreases as the frequency of macropores increases and the SW gradually increases as the frequency of small pores increases (Figure 9). This is related to the complexity of the pore structure of tight sandstone. The fractal dimension of large pores in tight sandstone is close to 3. According to fractal theory, the structure of macropores is more complicated than that of micropores in tight oil. Therefore, in the development of tight oil and gas, the impact of micropores on oil and gas seepage should be focused.

Figure 7 Fractal features of pore throat structure for tight sandstone samples.
Figure 7

Fractal features of pore throat structure for tight sandstone samples.

Table 3

Calculation results of fractal dimension with different intervals

SampleK/× 10−3 µm2φ/%DiR2Fi/µmTr/%DC
WB49-660.21611.22.73640.96990.0615–1.037550.122.6397
2.54250.97110.0036–0.061549.88
WB49-800.39312.02.66380.99320.0613–1.625263.832.5149
2.17530.98410.0036–0.061336.17
WB14-590.49711.22.66240.99580.0633–1.624082.102.7034
2.55660.91670.0035–0.063317.90
WB14-130.39912.12.65210.98730.0613–1.002169.822.6332
2.53940.99160.0035–0.061330.18
WB49-531.78510.52.60860.99250.0632–1.573574.262.5636
2.43390.93730.0035–0.063225.74
WB49-720.2029.12.56090.98430.0621–0.965158.312.4542
2.25770.99890.0035–0.062141.69
HH153-100.2238.32.66130.98260.0632–0.990667.672.4719
2.21280.99800.0036–0.063232.33
HH153-611.0410.62.73110.98290.0623–1.576163.352.5006
2.10230.99950.0035–0.062336.65
HH153-660.7699.82.70450.96910.0623–1.650666.412.6016
2.39830.98340.0035–0.062333.59
HH153-800.3417.62.71850.98790.0633–0.983755.132.4692
2.16300.99590.0035–0.063344.87
HH153-910.5309.52.68630.98790.0615–1.608762.712.4457
2.04110.95990.0035–0.061537.29
HH153-1000.2958.92.64970.98850.0602–1.032958.392.5811
2.48480.91130.0035–0.060241.61

φ, porosity; K, permeability; Di, fractal dimension corresponding to different scales of pore throats, i = L, macropore interval; i = S, micropore interval; Fi, different sizes of pore throats; Tr, ratio of pore throats at different sizes; DC, comprehensive fractal dimension

Figure 8 Relationship between permeability, porosity, and amplitude of pore distribution at different sizes. (a) the relationship curve between permeability and the amplitude of micropore and macropore; (b) the relationship curve between porosity and the amplitude of micropore and macropore.
Figure 8

Relationship between permeability, porosity, and amplitude of pore distribution at different sizes. (a) the relationship curve between permeability and the amplitude of micropore and macropore; (b) the relationship curve between porosity and the amplitude of micropore and macropore.

Figure 9 Relationship between Sw and distribution frequency of pore throats at different sizes.
Figure 9

Relationship between Sw and distribution frequency of pore throats at different sizes.

5.2 Comprehensive fractal dimension and its application

Different sizes of pore throat have various fractal dimensions (DS and DL). Various fractal characteristics reflect the different properties of micropore throat structure, indicating the complexity of the pore throat structure of the tight sandstone in the E Basin. Zhao et al. proposed to characterize the fractal features of tight sandstones using comprehensive fractal dimensions. Its calculation formula is as follows [6]:

(11)Dc=∑DiVi

where Dc is the comprehensive fractal dimension, dimensionless number; Di is the fractal dimension corresponding to the pore throat of different scales (macropores and micropores), namely DL and DS; Vi is the proportion of the pore throat corresponding to different fractal dimensions.

The Dc value calculated by equation (11) is between 2.4457 and 2.7034 with an average of 2.5483. Zhao et al. studied the comprehensive fractal dimension of tight sandstones in the Y Basin between 2.4294 and 2.6398, with an average of 2.5586 [6]. It can be found that the comprehensive fractal dimension of the tight sandstones in E Basin and Y Basin is basically same. And, the comprehensive fractal dimension values are close to the fractal dimension corresponding to the macropores (which fractal dimension is close to 3). Overall, the pore surface of the tight sandstone is rough, and the heterogeneity is serious. In addition, only the fractal dimension DL corresponding to macropores throat has a positive correlation with permeability, which indicates that macropores’ throat controls the permeability of tight sandstone (Figure 10b). There is no obvious correlation between DS and Dc and permeability (Figures 10b and c). These suggest that the storage space of the different sizes of pore throat strongly controls the fractal characteristic. However, there is a positive correlation between porosity and fractal dimension. With the increase of porosity, the fractal dimension increases to a certain extent (Figure 10a and d). The analyses described previously reveal that DL, DS, and the total fractal dimension presented different correlations with corresponding porosity and permeability. This suggests that the pore throat structure of E Basin tight oil sandstone is complex and pore throat sizes strongly affect the fractal characteristics of the pore throat and its homogeneity and complexity.

Figure 10 Relationship between fractal dimension (DL, DS, and Dc) and petrophysical properties of different sizes of pore throats.
Figure 10

Relationship between fractal dimension (DL, DS, and Dc) and petrophysical properties of different sizes of pore throats.

6 Conclusion

In this work, we employed TS and HPMI technology to characterize the pore throat structure of tight sandstone in the E Basin. In addition, we fitted the fractal dimensions of different scales and calculated the comprehensive fractal dimension based on the HPMI. According to the accomplished results, the following conclusions can be drawn:

  1. The tight sandstones of the E Basin have various types of cuttings, mainly metamorphic rocks and sedimentary rocks, including igneous rocks and mica, and soft cuttings are pseudo-matrices. In addition, the pore network of the tight oil sandstone mainly consists of primary pores, secondary pores, heterobasic pores, and microfractures.

  2. The pore throat radius of the E Basin is between 0.0035 and 2.6158 µm, and its heterogeneity is strong. The tight sandstone pore throat radius distribution curve has two peaks, and as the permeability increases, the pore throat size distribution curve gradually shifts to the right.

  3. The tight sandstones of the E Basin are characterized by segmentation fractals. According to the fractal features, the pores are divided into macropores (DL) and micropores (DS), and the values of the DL and DS are different. At the same time, the permeability and porosity are mainly contributed by the proportion of macropores, and the contribution of micropores to the permeability is relatively weak.

  4. The comprehensive fractal dimension (Dc) is calculated and no correlation is found between permeability and porosity. In addition, the Dc of tight sandstones in E Basin and Y Basin is compared and found to be similar. And, the size of the integrated fractal dimension is close to the fractal dimension of the macropore interval.

Acknowledgments

The authors are grateful to Yapu Zhang, Zhongkun Niu, and Xinliang Chen, Exploration and Development Research Institute of SINOPEC North China Company, for their help during the TS analyses. This study was financially supported by the National Science and Technology Major Project (2017ZX05013-001) and the R&D of PetroChina Company Limited (2019B-1311).

  1. Author contributions: Each author has made contributions to this paper. XLZ, ZMY, and XWL designed the experiments (HPMI and TS) and XLZ carried them out. XLZ, ZMY, XWL, and ZYW deduced the calculation formula of fractal dimension and fitted it with experimental data. XWL and YTL provide relevant insights into the part of the discussion. XLZ and XWL wrote and edited the manuscript. All authors have read and approved the final manuscript.

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Received: 2020-04-10
Revised: 2020-06-09
Accepted: 2020-07-13
Published Online: 2020-10-12

© 2020 Xinli Zhao et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/geo-2020-0121
Keywords for this article
tight sandstone; high-pressure mercury intrusion; thin section; pore throat structure; fractal dimension; E Basin
Creative Commons
BY 4.0

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  11. Geochronology, trace elements and Hf isotopic geochemistry of zircons from Swat orthogneisses, Northern Pakistan
  12. Regional-scale drought monitor using synthesized index based on remote sensing in northeast China
  13. Application of combined electrical resistivity tomography and seismic reflection method to explore hidden active faults in Pingwu, Sichuan, China
  14. Impact of interpolation techniques on the accuracy of large-scale digital elevation model
  15. Natural and human-induced factors controlling the phreatic groundwater geochemistry of the Longgang River basin, South China
  16. Land use/land cover assessment as related to soil and irrigation water salinity over an oasis in arid environment
  17. Effect of tillage, slope, and rainfall on soil surface microtopography quantified by geostatistical and fractal indices during sheet erosion
  18. Validation of the number of tie vectors in post-processing using the method of frequency in a centric cube
  19. An integrated petrophysical-based wedge modeling and thin bed AVO analysis for improved reservoir characterization of Zhujiang Formation, Huizhou sub-basin, China: A case study
  20. A grain size auto-classification of Baikouquan Formation, Mahu Depression, Junggar Basin, China
  21. Dynamics of mid-channel bars in the Middle Vistula River in response to ferry crossing abutment construction
  22. Estimation of permeability and saturation based on imaginary component of complex resistivity spectra: A laboratory study
  23. Distribution characteristics of typical geological relics in the Western Sichuan Plateau
  24. Inconsistency distribution patterns of different remote sensing land-cover data from the perspective of ecological zoning
  25. A new methodological approach (QEMSCAN®) in the mineralogical study of Polish loess: Guidelines for further research
  26. Displacement and deformation study of engineering structures with the use of modern laser technologies
  27. Virtual resolution enhancement: A new enhancement tool for seismic data
  28. Aeromagnetic mapping of fault architecture along Lagos–Ore axis, southwestern Nigeria
  29. Deformation and failure mechanism of full seam chamber with extra-large section and its control technology
  30. Plastic failure zone characteristics and stability control technology of roadway in the fault area under non-uniformly high geostress: A case study from Yuandian Coal Mine in Northern Anhui Province, China
  31. Comparison of swarm intelligence algorithms for optimized band selection of hyperspectral remote sensing image
  32. Soil carbon stock and nutrient characteristics of Senna siamea grove in the semi-deciduous forest zone of Ghana
  33. Carbonatites from the Southern Brazilian platform: I
  34. Seismicity, focal mechanism, and stress tensor analysis of the Simav region, western Turkey
  35. Application of simulated annealing algorithm for 3D coordinate transformation problem solution
  36. Application of the terrestrial laser scanner in the monitoring of earth structures
  37. The Cretaceous igneous rocks in southeastern Guangxi and their implication for tectonic environment in southwestern South China Block
  38. Pore-scale gas–water flow in rock: Visualization experiment and simulation
  39. Assessment of surface parameters of VDW foundation piles using geodetic measurement techniques
  40. Spatial distribution and risk assessment of toxic metals in agricultural soils from endemic nasopharyngeal carcinoma region in South China
  41. An ABC-optimized fuzzy ELECTRE approach for assessing petroleum potential at the petroleum system level
  42. Microscopic mechanism of sandstone hydration in Yungang Grottoes, China
  43. Importance of traditional landscapes in Slovenia for conservation of endangered butterfly
  44. Landscape pattern and economic factors’ effect on prediction accuracy of cellular automata-Markov chain model on county scale
  45. The influence of river training on the location of erosion and accumulation zones (Kłodzko County, South West Poland)
  46. Multi-temporal survey of diaphragm wall with terrestrial laser scanning method
  47. Functionality and reliability of horizontal control net (Poland)
  48. Strata behavior and control strategy of backfilling collaborate with caving fully-mechanized mining
  49. The use of classical methods and neural networks in deformation studies of hydrotechnical objects
  50. Ice-crevasse sedimentation in the eastern part of the Głubczyce Plateau (S Poland) during the final stage of the Drenthian Glaciation
  51. Structure of end moraines and dynamics of the recession phase of the Warta Stadial ice sheet, Kłodawa Upland, Central Poland
  52. Mineralogy, mineral chemistry and thermobarometry of post-mineralization dykes of the Sungun Cu–Mo porphyry deposit (Northwest Iran)
  53. Main problems of the research on the Palaeolithic of Halych-Dnister region (Ukraine)
  54. Application of isometric transformation and robust estimation to compare the measurement results of steel pipe spools
  55. Hybrid machine learning hydrological model for flood forecast purpose
  56. Rainfall thresholds of shallow landslides in Wuyuan County of Jiangxi Province, China
  57. Dynamic simulation for the process of mining subsidence based on cellular automata model
  58. Developing large-scale international ecological networks based on least-cost path analysis – a case study of Altai mountains
  59. Seismic characteristics of polygonal fault systems in the Great South Basin, New Zealand
  60. New approach of clustering of late Pleni-Weichselian loess deposits (L1LL1) in Poland
  61. Implementation of virtual reference points in registering scanning images of tall structures
  62. Constraints of nonseismic geophysical data on the deep geological structure of the Benxi iron-ore district, Liaoning, China
  63. Mechanical analysis of basic roof fracture mechanism and feature in coal mining with partial gangue backfilling
  64. The violent ground motion before the Jiuzhaigou earthquake Ms7.0
  65. Landslide site delineation from geometric signatures derived with the Hilbert–Huang transform for cases in Southern Taiwan
  66. Hydrological process simulation in Manas River Basin using CMADS
  67. LA-ICP-MS U–Pb ages of detrital zircons from Middle Jurassic sedimentary rocks in southwestern Fujian: Sedimentary provenance and its geological significance
  68. Analysis of pore throat characteristics of tight sandstone reservoirs
  69. Effects of igneous intrusions on source rock in the early diagenetic stage: A case study on Beipiao Formation in Jinyang Basin, Northeast China
  70. Applying floodplain geomorphology to flood management (The Lower Vistula River upstream from Plock, Poland)
  71. Effect of photogrammetric RPAS flight parameters on plani-altimetric accuracy of DTM
  72. Morphodynamic conditions of heavy metal concentration in deposits of the Vistula River valley near Kępa Gostecka (central Poland)
  73. Accuracy and functional assessment of an original low-cost fibre-based inclinometer designed for structural monitoring
  74. The impacts of diagenetic facies on reservoir quality in tight sandstones
  75. Application of electrical resistivity imaging to detection of hidden geological structures in a single roadway
  76. Comparison between electrical resistivity tomography and tunnel seismic prediction 303 methods for detecting the water zone ahead of the tunnel face: A case study
  77. The genesis model of carbonate cementation in the tight oil reservoir: A case of Chang 6 oil layers of the Upper Triassic Yanchang Formation in the western Jiyuan area, Ordos Basin, China
  78. Disintegration characteristics in granite residual soil and their relationship with the collapsing gully in South China
  79. Analysis of surface deformation and driving forces in Lanzhou
  80. Geochemical characteristics of produced water from coalbed methane wells and its influence on productivity in Laochang Coalfield, China
  81. A combination of genetic inversion and seismic frequency attributes to delineate reservoir targets in offshore northern Orange Basin, South Africa
  82. Explore the application of high-resolution nighttime light remote sensing images in nighttime marine ship detection: A case study of LJ1-01 data
  83. DTM-based analysis of the spatial distribution of topolineaments
  84. Spatiotemporal variation and climatic response of water level of major lakes in China, Mongolia, and Russia
  85. The Cretaceous stratigraphy, Songliao Basin, Northeast China: Constrains from drillings and geophysics
  86. Canal of St. Bartholomew in Seča/Sezza: Social construction of the seascape
  87. A modelling resin material and its application in rock-failure study: Samples with two 3D internal fracture surfaces
  88. Utilization of marble piece wastes as base materials
  89. Slope stability evaluation using backpropagation neural networks and multivariate adaptive regression splines
  90. Rigidity of “Warsaw clay” from the Poznań Formation determined by in situ tests
  91. Numerical simulation for the effects of waves and grain size on deltaic processes and morphologies
  92. Impact of tourism activities on water pollution in the West Lake Basin (Hangzhou, China)
  93. Fracture characteristics from outcrops and its meaning to gas accumulation in the Jiyuan Basin, Henan Province, China
  94. Impact evaluation and driving type identification of human factors on rural human settlement environment: Taking Gansu Province, China as an example
  95. Identification of the spatial distributions, pollution levels, sources, and health risk of heavy metals in surface dusts from Korla, NW China
  96. Petrography and geochemistry of clastic sedimentary rocks as evidence for the provenance of the Jurassic stratum in the Daqingshan area
  97. Super-resolution reconstruction of a digital elevation model based on a deep residual network
  98. Seismic prediction of lithofacies heterogeneity in paleogene hetaoyuan shale play, Biyang depression, China
  99. Cultural landscape of the Gorica Hills in the nineteenth century: Franciscean land cadastre reports as the source for clarification of the classification of cultivable land types
  100. Analysis and prediction of LUCC change in Huang-Huai-Hai river basin
  101. Hydrochemical differences between river water and groundwater in Suzhou, Northern Anhui Province, China
  102. The relationship between heat flow and seismicity in global tectonically active zones
  103. Modeling of Landslide susceptibility in a part of Abay Basin, northwestern Ethiopia
  104. M-GAM method in function of tourism potential assessment: Case study of the Sokobanja basin in eastern Serbia
  105. Dehydration and stabilization of unconsolidated laminated lake sediments using gypsum for the preparation of thin sections
  106. Agriculture and land use in the North of Russia: Case study of Karelia and Yakutia
  107. Textural characteristics, mode of transportation and depositional environment of the Cretaceous sandstone in the Bredasdorp Basin, off the south coast of South Africa: Evidence from grain size analysis
  108. One-dimensional constrained inversion study of TEM and application in coal goafs’ detection
  109. The spatial distribution of retail outlets in Urumqi: The application of points of interest
  110. Aptian–Albian deposits of the Ait Ourir basin (High Atlas, Morocco): New additional data on their paleoenvironment, sedimentology, and palaeogeography
  111. Traditional agricultural landscapes in Uskopaljska valley (Bosnia and Herzegovina)
  112. A detection method for reservoir waterbodies vector data based on EGADS
  113. Modelling and mapping of the COVID-19 trajectory and pandemic paths at global scale: A geographer’s perspective
  114. Effect of organic maturity on shale gas genesis and pores development: A case study on marine shale in the upper Yangtze region, South China
  115. Gravel roundness quantitative analysis for sedimentary microfacies of fan delta deposition, Baikouquan Formation, Mahu Depression, Northwestern China
  116. Features of terraces and the incision rate along the lower reaches of the Yarlung Zangbo River east of Namche Barwa: Constraints on tectonic uplift
  117. Application of laser scanning technology for structure gauge measurement
  118. Calibration of the depth invariant algorithm to monitor the tidal action of Rabigh City at the Red Sea Coast, Saudi Arabia
  119. Evolution of the Bystrzyca River valley during Middle Pleistocene Interglacial (Sudetic Foreland, south-western Poland)
  120. A 3D numerical analysis of the compaction effects on the behavior of panel-type MSE walls
  121. Landscape dynamics at borderlands: analysing land use changes from Southern Slovenia
  122. Effects of oil viscosity on waterflooding: A case study of high water-cut sandstone oilfield in Kazakhstan
  123. Special Issue: Alkaline-Carbonatitic magmatism
  124. Carbonatites from the southern Brazilian Platform: A review. II: Isotopic evidences
  125. Review Article
  126. Technology and innovation: Changing concept of rural tourism – A systematic review
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