Pore structure evaluation in ultra-deep tight sandstones using NMR measurements and fractal analysis

https://doi.org/10.1016/j.petrol.2022.110180Get rights and content

Highlights

  • NMR T2 spectrum is used to divide pore structure type of ultra-deep sandstones.

  • Fractal behaviors of various pore structure are unraveled using NMR and fractal analysis.

  • Complex pore assemblages result in the high fractal dimension of Type II and III pore structure.

Abstract

The reservoir quality, pore spaces and pore size distributions of Bashijiqike sandstones in Kuqa depression were described by thin sections, SEM (scanning electron microscopy) analysis and nuclear magnetic resonance (NMR) tests. In order to quantitatively characterize the complexity of pore structure, NMR T2 (transverse relaxation time) spectrum was used for fractal analysis. This study unravels the relationships between petrophysical parameters, NMR parameters and fractal dimension of the ultra-deep tight sandstones. Primary intergranular pores are the main component of pore spaces, followed by secondary dissolution pores and micropores, and there contain microfractures. The NMR T2 spectra are either bi-modal or uni-modal distribution. The uni-modal T2 spectrum reflects uniform pore spaces. The coexistence of intragranular pores and intergranular pores leads to the bi-modal T2 spectrum. There is a positive correlation between fractal dimensions and T2gm (geometric mean of the T2 distribution). Consequently, four pore structure types are determined according to irreducible water content, T2gm, RQI (reservoir quality index), and the characteristics of individual pore structure are summarized. Because of the uniform pore space, Type I and Type IV have the lowest fractal dimensions. The structure of Type II and Type III are most heterogeneous due to their combination of intergranular and intragranular pores. The results help clarify the internal relationships between petrophysical parameters and microstructure, and have implications for pore structure evaluation of ultra-deep sandstones worldwide.

Introduction

Tight sandstones contain abundant oil and gas reserves, however, they have low porosity (<10%) and low permeability (intrinsic permeability<0.1mD) (Desbois et al., 2011; Gao and Li, 2015; Zou et al., 2012; Lai et al., 2018a). In addition, the tortuous systems containing intergranular, intragranular pores and micropores are the main features of tight sandstones. The pore throats have a wide range from nano-scale (<1 mm) to micro-scale (Rezaee et al., 2012; Desbois et al., 2011; Anovitz and Cole, 2015; Lai et al., 2018a; Liu and Ostadhassan, 2019; Wu et al., 2020). Pore structure, which includes geometry, size, connectivity and distribution of pore throat (Fu et al., 2015), determines the hydrocarbon migration and accumulation, and it plays a dominant control in reservoir quality evaluation (Anovitz et al., 2015; Xi et al., 2016; Lai et al., 2019; Gao et al., 2020; Yuan et al., 2021). The wide variations in reservoir quality of tight rocks are mainly attributed to the heterogeneous pore networks (Anovitz et al., 2015). Therefore the characterizations of pore structure in tight sandstones are important for enhancing hydrocarbon recovery (Schmitt et al., 2015; Lai et al., 2018a).

The Kuqa Depression is rich in natural gas resources (Liu et al., 2020). Many giant gas fields have been found in the Kuqa Depression recently, including the Kela 2, Awa, Bozi, Dabei, Keshen gas fields (Jin et al., 2008). However, the Kuqa depression is a reactivated foreland basin, and had undergone complex tectonic evolution histories (Liu et al., 2020; Zheng et al., 2020). Additionally, the main gas bearing formation is ultra-deeply buried (>6000 m), leading to a complex assemblage of pores spaces and tortuous pore throat structure. Therefore the application of various complementary methods and fractal theory in pore throat structure characterization are of great importance.

Laboratory NMR measurements, which commonly measure T2 transversal relaxation time distribution, provide continuous pore size distributions (Dillinger and Esteban, 2014; Daigle et al., 2014; Sigal, 2015; Wang et al., 2018; Yuan et al., 2018; Zhang and Zhang, 2021). Besides NMR porosity, FFI (free fluid index), BVI (bulk volume of irreducible water), T2cutoff (T2 value separating FFI and BVI), and T2gm can be derived from NMR measurements (Pape and Clauser, 2009; Meng et al., 2016; Wang et al., 2018, 2020). Therefore, a large number of parameters are provided directly or indirectly by NMR tests, including permeability, porosity, and fluid saturation. These parameters are important in reservoir characterization (Müller-Huber et al., 2016). In addition, NMR gives the insights into the fluid states and types (movable/producible fluids, bound fluids) (Müller-Huber et al., 2016; Wang et al., 2018; Fan et al., 2019; Zhang et al., 2020). Nondestructive and quantitative are two advantages of NMR measurements, and consequently NMR analysis is one of the most commonly used methods for pore structure evaluation (Golsanami et al., 2016; Li et al., 2017; Wang et al., 2018; Wu et al., 2020).

Fractals are virtual, self-similar geometrical objects (Cai et al., 2010; Lai and Wang, 2015; Kulesza and Bramowicz, 2014). Fractal property is one of the characteristics of sandstone pore throat systems, which appears independent of scales (Lai et al., 2016; Yuan and Rezaee, 2019). Fractal theory helps build up the bridges between microscopic morphology and macroscopic performances (Kleinberg et al., 1994; Cai et al., 2010; Wang et al., 2012, 2018; Daigle and Johnson, 2016; Zhang et al., 2018). It is widely used for quantitatively characterizing heterogeneity of pore throat structure (Li and Horne, 2006; Li, 2010a, b; Wang et al., 2018; Yuan and Rezaee, 2019; Lai et al., 2019; Zhang et al., 2020). Lai et al. (2018b) firstly proposed a new model from NMR T2 spectrum, which can be used to derive the fractal dimensions. This model is widely used to quantitatively characterize the pore size and distribution. (Zhang et al., 2020; Zhang and Hu, 2020; Lu and Liu, 2021).

In this study, the pore structure of Bashijiqike ultra-deep tight sandstones is described by means of petrophysical measurements and fractal theory. The NMR T2 spectrum, NMR parameters as well as fractal dimension are used for pore structure evaluation. The study characterizes the connection between microscopic pore structure and fractal dimensions, and unravels the link between microscopic pore structure and macroscopic behaviors. In addition, the characteristics of various pore structures are summarized. The work is helpful for improving the scientific understanding of pore structure distribution and has practical implications for pore structure evaluation of ultra-deep tight sandstones, and is hoped to provide reference for pore structure evaluation and fractal analysis of sandstones worldwide.

Section snippets

Geological setting

The Kuqa depression is situated in the transition zone between Tarim Basin and southern Tianshan (Fig. 1) (Shi et al., 2004; Zou et al., 2006; Zeng et al., 2010; Feng et al., 2018; Zheng et al., 2020; Lai et al., 2021). The Kuqa depression is a foreland depression, which is formed during the Mesozoic to Cenozoic time (Shi et al., 2004; Zhang and Huang, 2005; Zeng et al., 2010; Nian et al., 2016). Due to the complex evolutionary history (Nian et al., 2016; Ju and Wang, 2018; Neng et al., 2018),

Methodology

In the model of calculating fractal dimensions using NMR measurement fist proposed by Lai et al. (2018b), it is based on the assumption that the pore systems are spherical. Thus, the equation containing the pores numbers (Ni) and size of pores ri (T2i value) can be written in (Eq. (1)) (Sigal, 2015; Zhang et al., 2020).Ni=Vpi43πri3=Vpi36π(ρT2i)3

Vpi (%) is the incremental pore volume amplitudes at specific T2 (T2i, ms), ri is the pore size, and ρ is surface relaxivity (μm/ms).

Then N(>ri), which

Pore spaces, porosity and permeability

According to core analysis, the minimum porosity is 1.26% and the maximum porosity is 14.69%, and the average porosity is 7.30%, while 0.017 to 133.0 mD is the wide range of permeability, with an average of 2.042 mD (Fig. 2). Most of the data points in the permeability versus porosity crossplot fall in the area with air permeability less than 1 mD and porosity less than 10% (Fig. 2). Therefore the Bashijiqike Formation in the Bozi wellblock of Kuqa depression is ultra-deeply buried tight

Discussion

In this section, the internal relationships between pore structure, reservoir quality and fractal dimension are unraveled using NMR tests and fractal analysis for the ultra-deeply buried (>6000 m) in Kuqa depression.

The permeability is commonly related to total porosity, indicating that the pore spaces of the samples using in this study are dominantly pores, but not fractures (Fig. 2). The NMR T2 distribution also confirm this due to the rareness in tail distribution and long T2 components

Conclusions

The porosity of Bashijqike sandstones in Bozi Wellblock of Kuqa depression is between 1.26% and 14.69%, and the average value is 7.30%, while permeability is from 0.017 to 133.0 mD, and the average value is 2.042 mD. The pore system includes residual intergranular pores, grain intragranular dissolution pores, micropores, fractures or microfractures. The NMR T2 spectra have two types: bi-modal and uni-modal distribution. The uni-modal T2 spectrum behaviors indicate that pore spaces are mainly

Author contribution statement

Yi Xin: Conceptualization, Methodology, Software, Writing- Reviewing and Editing; Guiwen Wang: Conceptualization, Methodology, Software, Software, Validation, Writing- Reviewing and Editing; Bingchang Liu: Data curation, Writing – original draft preparation; Yong Ai: Data curation, Writing – original draft preparation; Hongkun Liu: Data curation, Writing – original draft preparation; Deyang Cai: Data curation, Writing – original draft preparation; Shuwen Yang: Software, Validation; Yuqiang Xie:

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work is supported by National Science & Technology Major Project of China (No. 2017ZX05008-004-001). We thank the three anonymous reviewers for their constructive comments, which improve the paper significantly. The authors thank the handling editors of JPSE for their kind work on this paper. We also thank Rouhi Farajzadeh, the Executive Editor for his enthusiasm, patience, and tireless efforts.

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