Scholarly article on topic 'A discussion on the interrelationships between five properties in reservoir evaluation'

A discussion on the interrelationships between five properties in reservoir evaluation Academic research paper on "Earth and related environmental sciences"

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{"Reservoir (rock)" / Pores / Fractures / Vug / "Pore space" / Evaluation / "Geometrical property" / Lithology / "Physical property" / "Fluid property" / Resistivity}

Abstract of research paper on Earth and related environmental sciences, author of scientific article — Liangxiao Zhao, Mingjiang Chen

Abstract Reservoir pore spaces (incl. pores, fractures and vugs) are too complex to be predicted by use of the traditional interrelationships between the four properties of reservoirs, thus more and more contradictions occur in reservoir evaluation. A great number of case studies were made to reveal the causes of these contradictions and the corresponding solutions were also proposed. For the reservoirs with complex pore spaces, we found four common types of contradictions between porosity and permeability, porosity and water saturation, absolute permeability and effective permeability, and electrical property and hydrocarbon property. These contradictions are mainly caused by variation of pore types, pore-throat sizes and fracture occurrence. On this basis, the concept of geometrical property was presented and methods were discussed for qualitatively or quantitatively describing the geometrical properties of pores, fractures and vugs. The following findings were achieved. (1) For pores, two relationships were established between pores & throat sizes and rock textures, physical property & fluid property, and between pore types and fluid property & logging responses. (2) For fractures, five relationships were established between occurrence and pore texture index (m), radial extension and deep/shallow borehole resistivity, openness and fracture permeability, occurrence and matrix water saturation, and between development index and lithology. (3) For vugs, two relationships were established between size & connectivity and m value & three porosities derived from logging responses (neutron, density and sonic wave), and filling degree and logging responses. The interrelationships between geometrical property, lithology, physical property, fluid property and electrical property can significantly improve the evaluation of complex reservoirs such as carbonates.

Academic research paper on topic "A discussion on the interrelationships between five properties in reservoir evaluation"

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Research article

A discussion on the interrelationships between five properties in

reservoir evaluation

Zhao Liangxiao, Chen Mingjiang*

Geological Exploration and Development Research Institute of Chuanqing Drilling Engineering Co. Ltd., CNPC, Chengdu, Sichuan 610051, China

Received 18 July 2014; accepted 20 January 2015 Available online 2 September 2015

Abstract

Reservoir pore spaces (incl. pores, fractures and vugs) are too complex to be predicted by use of the traditional interrelationships between the four properties of reservoirs, thus more and more contradictions occur in reservoir evaluation. A great number of case studies were made to reveal the causes of these contradictions and the corresponding solutions were also proposed. For the reservoirs with complex pore spaces, we found four common types of contradictions between porosity and permeability, porosity and water saturation, absolute permeability and effective permeability, and electrical property and hydrocarbon property. These contradictions are mainly caused by variation of pore types, pore-throat sizes and fracture occurrence. On this basis, the concept of geometrical property was presented and methods were discussed for qualitatively or quantitatively describing the geometrical properties of pores, fractures and vugs. The following findings were achieved. (1) For pores, two relationships were established between pores & throat sizes and rock textures, physical property & fluid property, and between pore types and fluid property & logging responses. (2) For fractures, five relationships were established between occurrence and pore texture index (m), radial extension and deep/shallow borehole resistivity, openness and fracture permeability, occurrence and matrix water saturation, and between development index and lithology. (3) For vugs, two relationships were established between size & connectivity and m value & three porosities derived from logging responses (neutron, density and sonic wave), and filling degree and logging responses. The interrelationships between geometrical property, lithology, physical property, fluid property and electrical property can significantly improve the evaluation of complex reservoirs such as carbonates.

© 2015 Sichuan Petroleum Administration. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Reservoir (rock); Pores; Fractures; Vug; Pore space; Evaluation; Geometrical property; Lithology; Physical property; Fluid property; Resistivity

ELSEVIER

Traditionally, the so-called four properties in reservoir evaluation are lithology, physical property, hydrocarbon property and electrical property [1]. The interrelationships between the four properties have been used as the most important basis of reservoir evaluation for several decades in China. However, for reservoirs with complex pore systems, many contradictions between the four properties occur, which bring new challenges to petrophysicists and reservoir engineers [2]. The relationships between porosity and permeability, absolute permeability and effective permeability, porosity and water saturation, hydrocarbon property and height of oil column, fluid type (oil or

* Corresponding author. E-mail address: cmj21@sina.com (Chen MJ).

Peer review under responsibility of Sichuan Petroleum Administration.

water) and resistivity become much more complex in reservoirs with complex pore systems, which make it hard to evaluate reservoirs accurately [3—5]. This can be attributed to the complex geometrical property of pore systems [6,7]. Based on the analysis of the contradictions occurring between the four properties, the geometrical property of pore system is introduced as the fifth property in reservoir evaluation in this paper, which gives a feasible solution to the contradictions and opens up a new way for complex reservoir evaluation.

1. Contradictions between the four-property relationships in reservoir evaluation

Lithology is the macroscopic nature of mineral content, texture, structure and color of rocks [8]. Physical property

http://dx.doi.org/10.1016/j.ngib.2015.07.002

2352-8540/© 2015 Sichuan Petroleum Administration. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

refers to porosity, and absolute/effective/relative permeability. Hydrocarbon property refers to the saturation, distribution and occurrence of hydrocarbons in rocks. Electrical property refers to the responses of logging data, including resistivity, dielectric constant, acoustics, and nuclear [9].

The above four properties interrelate with and interact on each other, and they jointly decide the nature of a reservoir. Traditional interrelationships between them are established based on heterogeneous isotropic porous medium which is dominated by interconnected intergranular pores. Therefore, the relationships between porosity and permeability, absolute permeability and effective permeability, porosity/water saturation and logging responses are simple and stable. The reservoir parameters, such as porosity, permeability and water saturation, can be predicted reliably by using well logs. Thus, we can make an accurate evaluation on such reservoirs [10,11].

However, reservoirs are not only dominated by pores but also by fractures and vugs. Especially for carbonate reservoirs, their properties are extremely distinct due to the types and geometry of pores. In this case, the traditional interrelationships between the four properties become much more complex and some contradictions occur.

1.1. Relationship between porosity and permeability

Because of the variation of pore types and presence of fractures and vugs, permeability correlates poorly with porosity in the semi-logarithmic coordinate system. For the same porosity, the permeability may vary over several orders of magnitude. Fig. 1a shows a well-log plot of a well in Ahdeb Oilfield, Iraq. It can be seen that in interval between 2617 and 2656 m, porosity varies slightly between 21% and 28%, but permeability varies greatly between 0.2 mD and 1042.0 mD with a clear decrease from top to bottom. Fig. 1b shows the crossplot of permeability vs. porosity of the same well with Fig. 1a. It reveals that permeability also correlates poorly with

porosity, and it is impossible to build a unique permeability vs. porosity regression model. This is not only because of the presence of vugs, but also the variation of pore types and pore sizes in matrix.

1.2. Relationship between porosity and water saturation

Bulk volume water (BVW) is the product of porosity multiplied by water saturation (4 x Sw). For a reservoir with similar pore types and pore sizes, BVW is the function of the height above free water level and is a constant above the transition zone. If the porosity is plotted with water saturation on a crossplot, a hyperbolic trendline can be seen, as is shown in Fig. 2a. However, if there are more than one pore type or in presence of fractures or vugs, the data points may be scattered, as is shown in Fig. 2b. This is why this kind of crossplot cannot be used to identify movable water in some reservoirs with complex pore systems.

1.3. Relationship between absolute permeability and effective permeability

Reservoirs with large pores and throat sizes and high pore-throat ratios may have high absolute permeabilities but low relative and effective permeabilities, while reservoirs with small pores and throat sizes and low pore-throat ratios may have low absolute permeabilities but high relative and effective permeabilities. This is why some reservoirs with high core or log-derived permeability and porosity produce little or no fluids. Fig. 3 shows an example of this contradiction in a carbonate formation in a well in the central block of Pre-Caspian basin, Kazakhstan. The average porosity is about 8% and the permeability varies between 10 mD and 20 mD. Fig. 3a is the porosity-resistivity crossplot indicating that the reservoir is 100% water saturated. Fig. 3b is the porosity-water saturation crossplot which shows no movable water but

Fig. 1

a. Log plot

Log plot and crossplot of porosity vs. permeability of a well in Ahdeb Oilfield, Iraq (1 in = 25.4 mm; 1 ft = 0.3048 m).

5% 10% 15% 20% 25% 30% 35% 5% 10% 15% 20% 25% 30% 35%

Porosity Porosity

Fig. 2. Crossplot of porosity vs. water saturation of a carbonate reservoir in the Ahdeb Oilfield, Iraq.

presents as oil zone. Fig. 3c reflects low ejection efficiency. No fluids were produced from this formation before acid fracturing, while only little gas was produced after acid fracturing. A comprehensive analysis shows that this formation is a dry layer with high irreducible water saturation, high pore-throat ratio and low effective permeability.

1.4. Relationship between electrical property and hydrocarbon property

In some pore-type reservoirs, small and even pore sizes and low pore-throat ratios may correspond to high irreducible water saturation and very low resistivity, but the reservoirs can still produce pure oil and gas. In such cases, they may be mistaken for water zones by conventional logging analysis. Fig. 4a shows the log of a well in Bamai, Xinjiang, China. Interval between 4308 and 4310 m is a Carboniferous dolomite reservoir with resistivity as low as 3 U • m (close to that of underlying water zone), for which the P1/2 curve is straight and low slope, as is shown in Fig. 4b, which indicates a typical water zone. Test result shows gas production of 11.5 x 104 m3/ d. The thin section in Fig. 4c shows that the dolomite crystals are very fine and the pores between crystals are also very small and even, which leads to a high irreducible water saturation and low formation resistivity.

In the fracture-type reservoirs, the presence of a single set of low-angle or high-angle fractures may lead to the distortion of resistivity. Fig. 5 shows the log of a well in the Sichuan Basin, China. The upper interval between 4331 and 4344 m reveals relatively low resistivity and RLLD (Deep resistivity) lower than RLLS (Medium resistivity), while the lower interval between 4360 and 4370 m reflects relatively high resistivity and RLLD greater than RLLS. According to conventional logging interpretation theory, RLLD < RLLS implies water zone, while Rlld > Rlls implies hydrocarbon-bearing zone. It is easy to mistake the upper interval for water zone and the lower interval as hydrocarbon-bearing zone. Clearly, this is not the fact. The fracture identification logging indicates the presence of low-angle fractures in the upper interval and high-angle fractures in the lower interval, resulting in low resistivity in upper interval and high resistivity in lower interval. Therefore,

only if the occurrence of fractures is known to correct the resistivity, can we make accurate interpretation of fluid type of such a reservoir.

All the examples mentioned above indicate that it is the complex pore system that leads to the contradictions between the four properties in reservoir evaluation. If not solved, such contradictions will certainly impede the further expansion of reservoir logging evaluation. Therefore, the fifth property, pore space geometrical property, is proposed. Its relations with the four properties will be discussed.

2. Interrelationships between the five properties

The pore space of reservoir rocks includes pores, fractures and vugs. They have different geometrical characteristics that affect reservoir properties in different manner and extent. So, it is necessary to establish its relationships with the four properties.

2.1. Relationships between geometrical property of fracture and the four properties

2.1.1. Fracture occurrence vs. pore texture index (m)

The cementation factor, m, in Archie's equation is in fact related to the pore texture of rocks, which physically means the change rate of cross sectional area of electrically conductive path. Therefore, this m value can be considered as the pore texture index. Fractures can be classified into low-angle fractures, high-angle fractures and network fractures. They have great effect on the pore texture index m. According to theoretical studies and practical applications, for the fracture-type reservoirs, the m value ranges within 1.1 — 1.5 — close to 1.1 for low-angle fractures, close to 1.5 for high-angle fractures, and approximately 1.3 for network fractures.

2.1.2. Extension depth of fracture vs. depth detection resistivity

Extension depth of fracture refers to the distance that the fracture extends from borehole wall to deep formation. It is an important factor used to evaluate how fractures contribute to productivity. By shallow/deep lateral logging depth, the

1% 10% 100% 5% 10% 15% 20% 0.9 0.7 0.5 0.3 0.1

Porosity Porosity Mercury saturaion

Fig. 3. Logging responses and intrusive mercury curves of a Carboniferous carbonate reservoir in the central block of the Pre-Caspian Basin, Kazakhstan.

extension depth of fracture can be classified into four levels: deep extension (greater than 2 m), medium extension (between 0.5 m and 2.0 m), shallow extension (between 0.3 m and 0.5 m), and ultra-shallow extension (less than 0.3 m). Such levels of extension depth correspond to different deep lateral resistivity (Rd) and shallow-deep lateral resistivity ratio (RD/ Rs). Fig. 6 shows an example of identifying extension depth of fractures in Ordovician, Tarim Basin, China. In this example, the data points indicate a medium to shallow extension depth (0.3—2.0 m) of fractures.

2.1.3. Fracture openness vs. permeability

For fractures with different occurrences, the following equations can be used to calculate their permeability.

For single set fracture-type reservoirs,

Kf = 5.66 x 10

4Rd2 f

Kf = 8.5 x 10~4Rd24fm

For multi-set fracture-type reservoirs,

Kf = 4.24 x 10~4Rd24fm

For network fracture-type reservoirs,

where, R is a factor that is closely related to the extension depth of a fracture. If the extension depth is greater than 2—3 m, R = 1; if the extension depth is between 0.5 m and 2 m, R = 0.8; if the extension depth is between 0.3 m and 0.5 m, R = 0.4; if the extension depth is less than 0.3 m, R = 0. The factor d is the openness of a fracture, mm; m is the porosity index; 4f is fracture porosity.

2.1.4. Fracture occurrence vs. water saturation in matrix

The occurrence, density and porosity of fractures may have an effect on water saturation of the matrix cut by fractures and consequently on the resistivity. The following equations can be used to calculate water saturation of the matrix.

,„mb cnb .„mf

4b Swb , 4f

mb nb mf

4b Sx _ 4f

Fig. 4. Logging response and thin section of a Carboniferous carbonate reservoir in Bamai, Xinjiang, China.

Fig. 5. Logging response of carbonate reservoir in a well in the Sichuan Basin, China.

Rmf Sx Rw S,

S S1/2 Sx — Swb

where, 4b is matrix porosity; Sx and Swb are water saturations of flushed zone and matrix respectively; K1 is the correction coefficient of fracture occurrence; Rw, Rm, Rmf and Rmix are the resistivity of formation water, mud, mud filtrate and mixed fluid in flushed zone respectively, U • m.

2.1.5. Development index of fractures vs. lithology

A lot of actual data shows that the development index of fractures is closely related to the mineral content and grain size of rocks. In Fig. 7a, it is seen that quartz has the highest index and limestone has the lowest index, while dolomite and calcareous sandstone have index values between that of quartz and limestone. Fig. 7b shows the correlation between the development index of fractures and grain size. It is obvious that the smaller the grain size, the higher the index value for

Fig. 6. Crossplot of extension depth of fractures in Ordovician, Tarim Basin, China.

Fig. 7. Crossplot of fracture development index vs. lithology and grain size.

both dolomite and limestone. Dolomite has the higher possibility of fracture development than limestone.

2.2. Relationships between geometrical property of vugs and the four properties

Geometrical property of vugs refers to the size, intercon-nectedness and degree of filling of vugs.

2.2.1. Size and interconnectedness of vugs vs. pore texture index (m)

In general, vug-type reservoirs may have relatively higher m value than fracture-type or pore-type reservoirs. The m value for vug-type reservoirs can vary greatly from 2.0 to 5.0, which depends on the sizes and interconnectedness of vugs. The larger the size and poorer the interconnectedness, the greater m value is. For reservoirs dominated by vugs with good interconnectedness, the m value varies between 2.0 and 2.5, for those with poor interconnectedness, the m value varies between 2.5 and 3.0, and for those reservoirs dominated by separate vugs, the m value is greater than 3.0.

2.2.2. Size and interconnectedness of vugs vs. three logging porosities

For rocks dominated by medium or small-sized vugs with good interconnectedness, there is little difference between neutron porosity, density porosity and acoustic porosity, but acoustic porosity is slightly lower than neutron porosity and density porosity. For those with poor interconnectedness, acoustic porosity is significantly lower than neutron porosity and density porosity, especially when the interconnectedness becomes poorer. In the case of huge vugs, none of the porosity logs can be used to represent the actual porosity of the rocks, and instead the length of well-diameter expanded section can only be used to approximate the size of vugs.

2.2.3. Filling degree of vugs vs. logging responses

Effectiveness of vugs is not only related to interconnectedness but also to filling degree. So, it is necessary to establish the relationship between filling degree and logging responses.

CGR/ API

Fig. 8. Crossplot of shale in vugs and filling

2 -.-.

1 10 100

CGR/ API

in Ordovician, Yubei area, Xinjiang, China.

Image logs can be used to identify the filling of electrically nonconductive minerals. However, if vugs are filled by electrically conductive shale, conventional well image logs will not be valid. In this case, logging data that can be used to identify shale content and properties are required to distinguish the shale deposited normally from the shale in vugs and also to evaluate the proportion of shale in vugs. For this purpose, the Th/K content obtained by spectra gamma ray can be crossploted with neutron porosity or resistivity. For normally-deposited shale which suffer from overburden pressure, the neutron porosity decreases and the resistivity increases with the compaction degree. Regardless of the influence of porosity, the neutron porosity and resistivity are well correlated to shale content in formation. In other words, the neutron porosity increases and the resistivity decreases as the shale content (or CGR) increases. This feature is basically stable in the same block (as is shown by the trendline in Fig. 8). For shale in vugs, the points at which CGR is intersected with neutron porosity and resistivity will deviate greatly from this trendline in an increasing extent with filling degree.

is low, and the porosity is well correlated to permeability. RT2 is also mainly micrite, for which the pore and throat are poorly sorted, the throat size is small, microfractures exist, and the porosity is poorly correlated to the permeability. RT3 is dominated by micrite, for which the pore and throat are well sorted, no microfractures exist, and the porosity is well correlated to the permeability. RT4 is dominated by micro-crystalline particles and subordinated by micrite, with certain fractures and vugs, for which the pore and throat are poorly sorted and the porosity is poorly correlated to the permeability. RT5 is dominated by micrite with mainly intergranular pores, for which the pore and throat sizes are large, corresponding to high-permeability and good porosity-permeability relationship.

2.3.2. Pore/throat size vs. fluid property

Both capillary pressure and relative permeability experiments show that the smaller pore and throat size, the larger specific surface area, thus higher irreducible water saturation, larger pore-throat ratio, and higher residual hydrocarbon saturation.

2.3. Relations between geometrical property of pores vs. the four properties

The geometrical property of pores refers to the size, shape and distribution of pores and throats.

2.3.1. Pore/throat size vs. rock texture/physical property

Pattern of the capillary pressure curve reflects the size and distribution of throats in rocks. Throats are classified by the pattern, and the relationship between pore/throat size and rock texture or physical property is established through thin section analysis and with porosity and permeability taken into consideration. In the block of right bank of the Amu-Darya River, Turkmenistan, the carbonate reservoirs are characterized by multiple rock types, strong heterogeneity and complex pore system [12,13]. Based on pore/throat size and distribution and lithofacies, the reservoir rocks are classified into five rock types, as is shown in Fig. 9. RT1 is micrite with a spot of microcrystalline particles, for which the pore and throat are well sorted, but the pore/throat size is small, the permeability

2.3.3. Pore type vs. fluid property or logging response

Many authors have classified reservoir pore types for different purposes [14,15]. However, for petrophysical evaluation of reservoirs, we classify reservoir pores into separate pores and connected pores, in order to effectively establish the relationship between logging response and pore types. Separate pores include intragranular, modic and visceral foramen pores. Connected pores include intergranular, intercrystal, framework and intergranular dissolved pores. For rocks dominated by connected pores, fluid property is well correlated to logging response, namely, resistivity increases with the increase of water saturation and porosity. For rocks dominated by separate pores, fluid property is poorly correlated to logging response. For example, some water zones may exhibit high resistivity, low interval transit time and low density. It is easy to mistake such zones for hydrocarbon-bearing reservoirs.

Pores, vugs and fractures are treated separately because it is easier to establish the relationships between their geometrical properties and the four properties. However, there are also

Fig. 9. Pore-throat size, porosity-permeability relationship and thin sections of different rock types in carbonate reservoirs in the right bank of the Amu-Darya River, Turkmenistan.

many reservoirs containing a combination of pores, vugs and fractures, but this is beyond the scope of this paper.

3. Conclusions

reservoir evaluation. Only the geometrical properties of pores, fractures and vugs are understood and correlated to the four properties, can we make accurate evaluation to such complex reservoirs.

Carbonate reservoir is a big challenge to all petrophysicists and reservoir engineers, because its pore system is so complex that many contradictions occur between the four properties in

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