Pore-scale modeling of carbonates

Mehmani, Ayaz; Verma, Rahul; Prodanović, Maša

doi:10.1016/j.marpetgeo.2019.104141

Cited by 49 publications

(25 citation statements)

References 186 publications

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“…(1) Intergranular pore implies primary porosity. Intergranular pores refer to the pores between particles, matrix, and cement, pores supported by particles or matrix, and intergranular residual pores with a reservoir property that is not fully filled with matrix and authigenic cement [55,56]. The studied Xiagou Formation is in the late diagenetic stage.…”

Section: Reservoir Pore Types the Xiagou Formation In Qingximentioning

confidence: 99%

Pore Structure Characteristics of Tight Carbonate Reservoir in Qingxi Sag, Jiuquan Basin

et al. 2021

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The Xiagou Formation is the main tight oil reservoir in Qingxi Sag of Jiuquan Basin. Given the poor physical properties and other factors restricting tight oil exploitation and production in this area, studies should focus on microscopic pore structure characteristics. In this study, a nano-CT scanner, a SEM, and an NMR were used to study the pore structure characteristics of a tight carbonate reservoir in Qingxi Sag, Jiuquan Basin. The Xiagou Formation reservoir mainly consists of gray argillaceous dolomite and dolomitic mudstone. The pore categories are mainly elliptic, irregular, intergranular, and intragranular and mostly filled with clay and carbonate cement. Pore space is small, the intergranular or organic pores are mostly separated, and pore-throat is weakly connected. The throats mostly develop with lamellar and tube bundle-like characteristics and with poor seepage ability. The pore-throats mostly span from nanometer to micrometer sizes, and pore diameters are mainly concentrated in the range of 0.01–0.1 and 1–10 μm. It is a unimodal pattern mainly composed of micropores, or a bimodal regular allocation dominated by micropores supplemented by macropores. The relationship between micropore (<0.1 μm) and macropore (>1 μm) content allocation and mean pore diameter strongly controls the permeability of reservoir rocks. When macropore content reaches more than 85%, or when pore content totals less than 3%, the permeability of a reservoir remarkably increases. At a higher ratio of the average finest throat sectional area and throat-pore of reservoir rock, the throat radius lies closer to the connecting pore radius, pore and throat connectivity improves, and reservoir seepage ability becomes stronger. Based on reservoir capacity and seepage ability, pore structures of the tight carbonate reservoirs in study area are classified into type I (small-pore–thin-throat), type II (thin-pore–thin-throat), and type III (microporous-microthroat) with rock permeability>0.1 mD, 0.05–0.1 mD, and <0.05 mD, respectively. The type I pore structure reservoir should be regarded as an indicator of tight oil “sweet spots” reservoir in the study area.

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Section: Reservoir Pore Types the Xiagou Formation In Qingximentioning

confidence: 99%

Pore Structure Characteristics of Tight Carbonate Reservoir in Qingxi Sag, Jiuquan Basin

et al. 2021

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“…Many reservoir rocks, notably carbonates and clay‐bearing sandstones, exhibit complex pore geometries with very wide pore size distributions. The petrophysical properties of such rocks often do not obey classical correlations (Prodanović et al., 2015; Shanley et al., 2004), spurring pore‐scale studies of their fluid flow behavior (Mehmani et al., 2020). This can be done based on images of the pore space, obtained with for example, micro‐computed tomography (micro‐CT) and (FIB‐)SEM imaging (Bera et al., 2011; Bultreys, De Boever, & Cnudde, 2016; Ciobanu et al., 2011; Cnudde & Boone, 2013; Wirth, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…These regions can then be imaged by higher‐resolution techniques, that are then correlated back to the lower‐resolution micro‐CT scan (De Boever et al., 2015; Devarapalli et al., 2017; Lin et al., 2019). The unresolved pores, which we will by definition refer to as the microporosity, can play a crucial role in the sample's multiphase flow behavior (Bultreys, Stappen, et al., 2016; Mehmani et al., 2020). Therefore, specialized multi‐scale models are required that fuse the resolved pores with information on the microporosity features, typically obtained using higher‐resolution images on small sub‐sections of the sample (Menke et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

Anchoring Multi‐Scale Models to Micron‐Scale Imaging of Multiphase Flow in Rocks

Wang

Ruspini

Øren

et al. 2022

Water Resources Research

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Image‐based pore‐scale modeling is an important method to study multiphase flow in permeable rocks. However, in many rocks, the pore size distribution is so wide that it cannot be resolved in a single pore‐space image, typically acquired using micro‐computed tomography (micro‐CT). Recent multi‐scale models therefore incorporate sub‐voxel porosity maps, created by differential micro‐CT imaging of a contrast fluid in the pores. These maps delineate different microporous flow zones in the model, which must be assigned petrophysical properties as input. The uncertainty on the pore scale physics in these models is therefore heightened by uncertainties on the representation of unresolved pores, also called sub‐rock typing. Here, we address this by validating a multi‐scale pore network model using a drainage experiment imaged with differential micro‐CT on an Estaillades limestone sample. We find that porosity map‐based sub‐rock typing was unable to match the micrometer‐scale experimental fluid distributions. To investigate why, we introduce a novel baseline sub‐rock typing method, based on a 3D map of the experimental capillary pressure function. By incorporating this data, we successfully remove most of the sub‐rock typing uncertainty from the model, obtaining a close fit to the experimental fluid distributions. Comparison between the two methods shows that in this sample, the porosity map is poorly correlated to the multiphase flow behavior of microporosity. The method introduced in this paper can help to constrain the sources of uncertainties in multi‐scale models in reference cases, facilitating the development of simulations in complex reservoir rocks important for for example, geological storage of CO2.

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“…These drawbacks grow with the resolu-tion of a pore structure. Pore-scale direct simulations of multiphase flows are costly and time-consuming [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Pore-Scale Characterization and PNM Simulations of Multiphase Flow in Carbonate Rocks

et al. 2021

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This paper deals with pore-scale two-phase flow simulations in carbonate rock using the pore network method (PNM). This method was used to determine the rock and flow properties of three different rock samples, such as porosity, capillary pressure, absolute permeabilities, and oil–water relative permeabilities. The pore network method was further used to determine the properties of rock matrices, such as pore size distribution, topological structure, aspect ratio, pore throat shape factor, connected porosity, total porosity, and absolute permeability. The predicted simulation for the network-connected porosity, total porosity, and absolute permeability agree well with those measured experimentally when the image resolution is appropriate to resolve the relevant pore and throat sizes. This paper also explores the effect of the wettability and fraction of oil-wet pores on relative permeabilities, both in uniform and mixed wet systems.

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Pore-scale modeling of carbonates

Cited by 49 publications

References 186 publications

Pore Structure Characteristics of Tight Carbonate Reservoir in Qingxi Sag, Jiuquan Basin

Pore Structure Characteristics of Tight Carbonate Reservoir in Qingxi Sag, Jiuquan Basin

Anchoring Multi‐Scale Models to Micron‐Scale Imaging of Multiphase Flow in Rocks

Pore-Scale Characterization and PNM Simulations of Multiphase Flow in Carbonate Rocks

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