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Article

Correlations between Petroleum Reservoir Fluid Properties and Amount of Evolved and Dissolved Natural Gas: Case Study of Transgressive–Regressive-Sequence Sedimentary Rocks

by
Ibtisam Kamal
1,2,
Namam M. Salih
3 and
Dmitriy A. Martyushev
4,*
1
Chemical Engineering Department, Faculty of Engineering, Soran University, Soran 44008, Kurdistan Region, Iraq
2
Basrah University College of Science and Technology, Basra 61004, Iraq
3
Petroleum Engineering Department, Engineering Faculty, Soran University, Soran 44008, Kurdistan Region, Iraq
4
Department of Oil and Gas Technologies, Perm National Research Polytechnic University, 614990 Perm, Russia
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2023, 11(10), 1891; https://doi.org/10.3390/jmse11101891
Submission received: 19 July 2023 / Revised: 12 September 2023 / Accepted: 22 September 2023 / Published: 28 September 2023
(This article belongs to the Section Geological Oceanography)
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Versions Notes

Abstract

:
It is well recognized that PVT data are essential in oil and gas production facilities as well as in the determination of the reservoir fluid composition in reservoir engineering calculations. In the current work, the studied borehole is located in Tawke oilfield in the High Folded Zone. The structural geology and lithological facies of rocks are studied and found to comprise fine crystalline dolomite and anhydrite interbedded with claystone and dolomite. In addition, the practical PVT data of black oil from Tawke oilfield, Zakho, from reservoirs to transgressive–regressive cycles, are studied. The PVT data are investigated to derive the empirical models that rule and correlate the properties of the reservoir fluids in terms of the amount of natural gas (methane, ethane, and propane) dissolved in reservoir fluids and evolving from the wells. The characteristics of the reservoir fluid, including °API, viscosity at reservoir pressure and bubble-point pressure, reservoir pressure and temperature, gas–oil ratio (GOR), coefficient of compressibility at reservoir pressure, gross heating value, and sample depth, are correlated. The lithological part reveals that the carbonate and some clastic rock facies are conducive to enhancing natural gas adsorption. The reservoir fluid properties show adverse effects on the amount of natural gas constituents evolving from the wells, while it shows positive effects on the dissolved reservoir fluids. The estimated empirical correlations can help indicate the quantity of natural gas that is dissolved in reservoir fluids and liberated from the wells depending on the characteristics of the reservoir. In addition, they can be used in numerical simulators to predict oil well performance.

1. Introduction

Fossil fuel natural gas is generated from the residues of microorganisms, plants, and animals. Between 70 and 90% of natural gas is generally methane (CH4). Carbon dioxide, and some other gases including ethane (C2H6), propane (C3H8), butane (C4H10), and hydrogen sulfide (H2S), besides small amounts of inert gases, form the rest of the composition. Natural gas composition diverges broadly as a function of source and time, leading to differences in thermodynamic and physical characteristics that influence its combustion and emissions performance [1]. Methane is a major component of natural gas and can be found in rock formations either as thermogenic or biogenic/bacterial methane. The organic matter buried at substantial depths where the rocks are compressed and heated aggressively turn into thermogenic methane, while biogenic methane forms nearer to the surface through bacterial action. Thermogenic natural gas typically contains 20–30% more methane than in biogenic methane. The complexity of the generation, accumulation, migration, and processes of natural gas leads to significant variation in the chemical and isotopic (particularly C and H) components of natural gas [2]. Distinguishing between coal-derived gas and oil-associated gas is commonly carried out using ethane carbon isotopes. It has been documented that for oil-associated natural gas, the δ13C2 < −29‰, while for coal-derived gas, it is >−29‰ [3]. Also, it is reported that there is a greater proportion of higher-chain hydrocarbons in thermogenic natural gas relative to that in microbial gas, which mostly contains methane and carbon dioxide [4]. The presence of microbially mediated pathways that produce hydrocarbons with two or more carbon atoms has previously been highlighted [5].
There are three broad categories for reservoir fluids: (i) gases (both hydrocarbon and non-hydrocarbon), (ii) liquid hydrocarbons, and (iii) aqueous solutions with dissolved salts. The reservoir fluids’ compositions are based on their history, source of the composition, and thermodynamic circumstances. The petrophysical characteristics of rocks and the thermodynamic conditions of the reservoir, besides the physical and chemical properties of the fluids, govern the fluids’ distribution within a given reservoir [6]. The pressure gradients, gravity, capillary, molecular diffusion, and thermal convection are forces that also control the fluids’ distribution [7].
The type of lithofacies and pressure–volume–temperature (PVT) data are considered the main characteristics describing the behavior of oil properties in any sedimentary reservoir. The significance of developing empirical correlations for estimating PVT characteristics when experimental data are unavailable has been paid considerable attention by researchers around the world. The PVT is analyzed in order to determine the behavior of reservoir fluid properties during different reservoir conditions. This type of analysis is applied to identify the dissimilarities in the volume and phase state that occur during oil production [8]. Some correlations derived from PVT datasets related to particular geographical regions are highlighted in the literature [9,10,11,12]. Yet, studies on the prediction of the relationships of natural gas content with reservoir features including the PVT data for crude oils in Kurdistan Region are rare. The literature lacks such studies, which are very important, especially since the design of the production facilities is usually based on PVT analysis.
The current study focuses on a newly developed reservoir for heavy oil production explored previously (2018) in the Kurdistan region of Iraq. The aim of the work is to analyze the effect of PVT properties and the lithostratigraphy of the reservoir rocks and to express the mathematical models that correlate and rule the properties of reservoir fluids in accordance with the amount of natural gas (methane, ethane, and propane) that is dissolved in reservoir fluids and that evolved from the wells.

2. Methodology

The reservoir fluid properties investigated are: (1) The dissolved gas amount in the oil at any pressure, namely, the gas–oil ratio (GOR) of the solution. It is a function of the oil and gas composition; heavy oils contain less dissolved gas than light oils, and range from 0 (dead oil) to approximately 2000 scf/bbl. The GOR increases approximately linearly with the pressure until reaching bubble-point pressure, and then the GOR becomes constant, where the oil is described as undersaturated. (2) Reservoir temperature. This is denoted as a mean temperature preserved in a reservoir. (3) Reservoir pressure, also known as hydrostatic pressure. When the pressure of the reservoir hydrocarbon fluids achieves bubble-point pressure, the reservoir becomes saturated and the bubbles within the reservoir increase as the pressure drops. The fluid flow becomes unstable and a pulsation effect in the pipeline structure occurs when the pressure is about 30% higher than bubble-point pressure [13]. (4) API defines the specific gravity by oAPI = (141.5/γo) − 131.5. (5) Reservoir fluid density at bubble-point pressure. The oil above bubble-point pressure tends to be undersaturated and acts as a single-phase liquid. Below this pressure, the oil tends to be saturated. A two-phase flow results when the pressure drops, leading to gas libration. (6) The viscosity of the oil, which represents the measure of oil resistance to flow in centipoises (cP). It decreases with increasing temperature and pressure (up to the bubble point), and then increases slightly with increasing pressure above the bubble point. The viscosity is significantly affected by oil gravity, GOR, and reservoir temperature. (7) Coefficient of compressibility at reservoir pressure, which is defined as the ratio of alteration in the pressure to the corresponding fractional change in the density or volume of the fluid at constant temperature. The precision of the high-pressure surface design and the measurement of material balance could be improved by the higher accuracy of oil compressibility estimates. (8) Gross heating value, which is the maximum potential energy available in a fuel sample, that is, the heat generated by the complete combustion of a unit volume of gas including the heat recoveries by condensing the water vapor formed.

3. Geological Setting

The Tawke anticline is located in the high folded zone within the Zagros Fold Belt. This belt was formed during the Eocene period through a stage of collision between the Eurasian plate and the Neo-Tethyan terrains. The subduction caused the subsequent closure of the Neo-Tethys Ocean. This subduction in the Zagros Fold Belt produced a complex structural setting around the study area, including faults such as strike-slip faults and dip faults, uplifting, and the dominance of fractures.
The Tawke anticline is characterized by complex tectonic features, high folds, asymmetrical folds, and several types of faults. It is characterized by a length of 27 km and a width of around 8 km. From the north, the Tawke anticline is attached to the Zakho Syncline and in the south, is attached to the Khabore Syncline (Figure 1).
The significant exposed rocks in the study belong to the Middle Miocene–Pliocene, besides Quaternary sediments. The sequence of the rocks start from the Gercus formation, which is the oldest formation belonging to the Middle Miocene, and move on to the Pila Spi Formation, the Lower and Upper Fars formations, and the Lower and Upper Bakhtiari formations.

4. Lithological Indicators of the Oil Wells

Tawke oilfield is located in the Kurdistan Region, Iraq. The studied area covers an area of approximately 25 km by 3 km. Tawke wells are drilled within a stratigraphic succession of Tertiary-aged sedimentary rocks (mostly Lower Fars and Jeribe formations).
The PVT data analyzed in the current work are prepared for samples taken from both Fars and Jeribe formations, as indicated from the presented litho-log of the oil wells [15]. The thickness of the Lower Fars Formation is about 160 m, while for the Jeribe Formation is around 50 m. A typical lithologic pattern for stratigraphic columns for one of the investigated wells is shown in Figure 2. The lithological features of the wells revealed that the mineral composition of the Lower Fars Formation consists predominantly of claystone and siltstone interbedded with sandstone and less-dominant anhydrite rocks. It is obvious that the Fars Formation overlies the Jeribe Formation. The litho-log shows that the Jeribe Formation is composed mainly of limestone interbedded with dolostone and claystone. Furthermore, the log shows a strong oil color and yellow fluorescence in limestone, gray, and light gray claystone in places interbedded with a lateral tongue of thin layers of siltstone. Since the claystone usually coexists with organic matter in the sedimentary rocks, the claystone is considered a good parameter to analyze the generation of hydrocarbon processes.
On the other hand, the lithologic pattern charts of the log show a laminated shale mudstone, which is one of the basic compositions of the rocks. Clay and organic material associated with shale play significant role in petroleum origin. The mineralogical composition of clay and shales associated with a high enough quantity of organic constituents cause adsorption, forming a dominant source material and, consequently, act as catalysts in oil/gas generation [16]. Furthermore, there is diagenesis of claystone and clay transformation during this stage (i.e., from montmorillonite to mixed-layer montmorillonite/illite, and then to illite). High contents of illite and mixed layers are conducive to enhancing gas or oil adsorption because the clays have strong adsorption capacity [17,18].

5. Results and Discussion

From the available DNO database, it is observed that the normal background level of the evolved natural gas constituents ranges from 75.7 to 79.7, 0.66 to 0.84, and 0.35 to 0.57 mole% for methane, ethane, and propane, respectively, while they range from 10.3 to 12.4 mole% for methane and about 0.18 mole% for both ethane and propane gases that are dissolved in reservoir fluid. These observations revealed that the majority of the evolved natural gas from the investigated targeted wells and that is dissolved in reservoir fluid is methane. Methane is represented as the largest natural gas component and is also about 165 times more potent than ethane.
Although the decomposition rate of organic compounds increases with the increase in the depth of the rock facies that are exposed to higher temperature and pressure, the geological factors, including the organic matter type, the rapid litho-changes in composition, the properties of the reservoirs (i.e., grain sizes, grain morphology, sorting), may also have a role in decreasing the amount of evolved natural gas with increasing depth.
The selected black oil samples were obtained from the Lower Fars and Jeribe formations. The former formation’s lithofacies characterizes the rapid litho-changes and dominant claystone–sandstone alterations, with repeated thin layers of anhydrite, and less frequent carbonates and siltstone (Figure 2). The depositional setting of the Lower Fars Formation is controlled by alternating periods of long-term dry and wet intervals that caused desiccation and influxes of fresh seawater [19]. The massive and hard cemented material ‘conglomerate’ is referred to as the significant transgression that introduces the Lower Fars. The regression followed at the Early Miocene, likely in the Kirkuk region, between the end of the Eocene and the end of the Lower Miocene; during this time, the Avanah limestone was exposed to continuous weathering and erosion.
The Jeribe Formation is characterized predominantly by dolomite rocks, and in places where dolomitic limestone also appears, the dolomite alternates with thin layers of anhydrite and claystone (Figure 1). Numerous and intense repeated cycles of gray and brown marls and flooded fragmented limestones, topped by evaporites and halite, define the Fatha Formation [20].
The authors define the Lower Fars Formation, which aged during the Miocene period, as a sequence of transgressive–regressive cycles in a wide, shallow foreland basin close to the Zagros–Taurus belt. The high-frequency cycles underlying the Lower Fars Formation also characterize this formation; however, the lithological composition and depositional setting are different (Figure 1). The Jeribe Formation comprises a dominant dolomite rock and less-frequent thin layers of anhydrites. The repeated cycles of dolostone with thin layers of anhydrite and claystone probably indicate a shallowing upward condition during the deposition of the Jeribe Formation (Figure 2). This cycling could be related to changes in the sea level during the depositional setting [21]. Furthermore, the entire Lower Miocene is absent in the west, over the Ga’ara high; however, the Euphrates limestone and Jeribe Formation are close to exposure to the Euphrates River, far beyond the occurrence of the Oligocene deposits, thus stressing the importance of the basal Miocene transgression, which could be strongly linked to major transgressive–regressive cycling between the Jeribe and Lower Fars formations.
The adsorption of methane in different kinds of mineralogical compositions that repeated in cycles, from the dominant clastic rocks alternating with anhydrites and limestone in the Lower Fars Formation and the frequent occurrence of carbonate rocks with thin layers of anhydrites in the Jeribe Formation, probably could have played a direct role in the development of the reservoir fluid properties.
Several researchers have reported that clays tend to increase the methane adsorption capacity [22,23], and highlighted a positive connection between the porosity measurement and specific surface area. Furthermore, the adsorption capacity of methane in a different kind of clay mineral was found, with the largest capacity being found for smectite, andradite kaolinite, and chlorite and the lowest capacity being recorded for illite [24,25]. However, the heterogeneity of carbonate rocks can cause a considerable amount of methane gas to be adsorbed [26,27].
Figure 3a shows that the amount of evolved gas decreases as the sample depth increases, while there is less significant increase in the relatively small amount of gas dissolved in reservoir fluid, as shown in Figure 3b,d. This may be attributed to increasing sediment deposition with increasing temperature and pressure at greater depths. The sediments tend to aggregate without losing their associated fluid; therefore, the amount of evolved gas decreases.
Figure 4b,d show that the amount of natural gas dissolved in reservoir fluids increases during an increase in the reservoir temperature. This proportional relationship could be attributed to increasing gas solubility and reservoir temperature, thus enhancing the degradation rate of organic compounds, leading to the formation of more dissolved gas in the reservoir. However, the phenomena are inversed for the evolved gases, as shown Figure 4a,c.
The amount of evolved gas decreased with the increase in the reservoir temperature. This may be attributed to an increase in the capacity of adsorption of the various kinds of clay mineralogical compositions, and the heterogeneity of carbonate rocks as a function of well depth and temperature. A similar trend is observed with the effect of reservoir pressure, as shown in Figure 5a,c. In the same vein, it has been pointed out that moisture content and salinity have a significant role in the adsorption of methane in kerogen [28,29,30].
Figure 6 illustrates how an increase in the quantity of natural gas dissolved in reservoir fluid resulted in an increased gas–oil ratio. This is reasonable, as the amount of dissolved gas in the reservoir fluid reflects the gas–oil ratio. Generally, as mentioned before in the Introduction section, black oils often have a lower gas–oil ratio compared to volatile oils [10,11].
The change in °API with the quantity of natural gas dissolved in reservoir fluid is shown in Figure 7a. It is obvious that as the amount of dissolved natural gas increases, a remarkable increase in °API is observed, while a decrease in density is recorded. The dissolving of light hydrocarbon gases other than carbon dioxide in reservoir fluids decreases the density and, consequently, increases the °API of the fluids. In general, petroleum density is denoted in terms of °API. There is an inverse relationship between °API and oil density; an increase in °API is generally accompanied by a decrease in oil density. Figure 7b shows the situation of the samples investigated.
From another perspective, oil viscosity is highly correlated with the engineering disciplines, such as the improvement of oil recovery, natural gas storage, the design of oil pipelines, compressors, and other equipment used in petroleum transportation, and the simulation of oil and gas reservoir production profiles [31]. The viscosity of the reservoir fluids at reservoir and bubble-point pressures seemed to increase with an increase in the amount of dissolved gas, as shown in Figure 8a–d, and a decrease in the well depth, as illustrated in Figure 8e. The situation is attributed to an increase in the temperature with an increase in the well depth.
Figure 9 demonstrates the change in the quantity of natural gas dissolved in reservoir fluid with the coefficient of compressibility. The outcomes obtained prove that the quantity of dissolved natural gas has a positive influence on the unit change of reservoir fluid volume with pressure at a constant temperature.
The amount of embedded energy in petroleum and its derived fuels is demarcated by the gross heating value (HHV). Figure 10 demonstrates the variation in the amount of evolved gas in terms of gross heating value. It was reported that there is high regression between HHVs and specific gravity for petroleum fuels. It was pointed out that increasing the specific gravity of petroleum fuels resulted in a regular decrease in HHVs [32,33,34]. The results obtained clarified that as the amount of evolved gas increases, there is a consequent HHV decrease.
Table 1 includes the adopted mathematical correlations estimated in this work. The correlations were estimated by linear regression using the graphical Microsoft Excel software. The regression coefficients are indicators that define the accuracy of the models in fitting the experimental data. It is obvious that most of the developed models have high regression coefficients; this indicates that the developed models can efficiently describe the experimental data [35,36,37]. The adopted mathematical models derived in this work suggest that the amount of natural gas that is evolved from, and dissolved in, reservoir fluids in the investigated region depend on the characteristics of the reservoirs. The derived mathematical equations are empirical and applicable for describing the PVT parameters related to the site under investigation.

6. Conclusions

The amount of natural gas from the oil wells of Tawke oilfield, Kurdistan, Iraq, is correlated with reservoir properties. The concentration of evolved methane is up to 79.7 mole%, while for the dissolved reservoir fluid is up to 12.4 mole%. A small concentration (less than 1 mole%) is recorded for evolved and dissolved ethane and propane. Thirty-eight adopted mathematical models were estimated. Most of the developed mathematical models displayed high fitting to the experimental data, reflected by the high values of the regression coefficients. The quantity of evolved natural gas appeared to decrease with the increasing depth of the samples and the temperature/pressure of the reservoir, while the amount of dissolved natural gas showed the inverse behavior. The °API, coefficient of compressibility at reservoir pressure, and the gas–oil ratio showed an increase with the amount of dissolved natural gas, while the viscosity decreased. A regular decrease in the gross heating value of the reservoir fluid was observed with an increasing amount of natural gas that evolved from the oil wells. The estimated mathematical models could be used to envisage the quantity of natural gas based on reservoir characteristics. Also, they can be used in numerical simulators to predict oil well performance. These data and the significant correlation between different kinds of parameters in reservoir rock were adapted to the periodic deposition of clastic and carbonate sedimentary rocks in the Fars and Jeribe formations during fluctuating sea levels that influenced repetitive and cyclic depositional settings for both formations.

Author Contributions

Writing and preparation the original draft, I.K. and N.M.S.; review and editing, N.M.S. and I.K.; Methodology and software, N.M.S., I.K. and D.A.M. visualization, N.M.S., I.K. and D.A.M.; supervision, N.M.S. and I.K.; project administration, N.M.S., I.K. and D.A.M. All authors have read and agreed to the published version of the manuscript.

Funding

The research was funded by the Ministry of Science and Higher Education of the Russian Federation (Project No. FSNM-2023-0005).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Acknowledgments are dedicated to the technical staff of DNO, and to the Norwegian oil and gas operator in the Kurdistan Region, Iraq, for providing the PVT data and the litho-log of the oil wells investigated in the study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kayadelen, H.K. Effect of natural gas components on its flame temperature, equilibrium combustion products and thermodynamic properties. J. Nat. Gas Sci. Eng. 2017, 45, 456–473. [Google Scholar] [CrossRef]
  2. Liu, Q.; Wu, X.; Wang, X.; Jin, Z.; Zhu, D.; Meng, Q.; Huang, S.; Liu, J.; Fu, Q. Carbon and hydrogen isotopes of methane, ethane, and propane: A review of genetic identification of natural gas. Earth-Sci. Rev. 2009, 190, 247–272. [Google Scholar] [CrossRef]
  3. Dai, J. Chapter 7—In Coal-Derived Gas Fields and the Gas Sources of Offshore China. In Giant Coal-Derived Gas Fields and Their Gas Sources in China; Academic Press: Cambridge, MA, USA, 2017; pp. 447–549. [Google Scholar]
  4. Schoell, M. The hydrogen and carbon isotopic composition of methane from natural gases of various origins. Geochim. Cosmochim. Acta 1980, 44, 649–661. [Google Scholar] [CrossRef]
  5. Stoupakova, A.V.; Korobova, N.I.; Mordasova, A.V.; Sautkin, R.S.; Sivkova, E.D.; Bolshakova, M.A.; Voronin, M.E.; Suslova, A.A.; Karpushin, M.Y.; Kozhanov, D.D.; et al. Depositional environments as a framework for genetic classification of the basic criteria of petroleum potential. Georesursy 2023, 25, 75–88. [Google Scholar] [CrossRef]
  6. Behbahani, T.J.; Dahaghin, A.; JafariBehbahani, Z. Experimental Investigation and Thermodynamic Modeling of the Phase Behavior of Reservoir Fluids. Energy Sources Part A Recovery Util. Environ. Eff. 2014, 36, 1256–1265. [Google Scholar] [CrossRef]
  7. Shuster, V.L.; Dzyublo, A.D. Substantiation of the prospects to discover large oil and gas accumulations in the Jurassic and pre-Jurassian deposits on the Kara Sea shelf. Georesursy 2023, 25, 67–74. [Google Scholar] [CrossRef]
  8. Mansour, E.M.; Farag, A.B.; El-Dars, F.S.; Desouky, S.M.; Batanoni, M.H.; Mahmoud, M.R.M. Predicting PVT properties of Egyptian crude oils by a modified Soave–Redlich–Kowng equation of state. Egypt. J. Pet. 2013, 22, 137–148. [Google Scholar] [CrossRef]
  9. El-Hoshoudy, A.N. Numerical prediction of oil formation volume factor at bubble point for black and volatile oil reservoirs using non-linear regression models. Pet. Petrochem. Eng. J. 2018, 2, 11. [Google Scholar]
  10. El-Hoshoudy, A.; Desouky, S. PVT Properties of Black Crude Oil. In Processing of Heavy Crude Oils—Challenges and Opportunities; Gounder, R.M., Ed.; IntechOpen: London, UK, 2019. [Google Scholar] [CrossRef]
  11. Alher, A.A.; Aljawad, M.S.; Alyasery, A.A. Estimating the PVT Properties for Crude Oil from a Southern Iraqi Oil Field. IOP Conf. Ser. Mater. Sci. Eng. 2018, 433, 012076. [Google Scholar] [CrossRef]
  12. Kamal, I.; Amjadian, K.; Salih, N.; Ahmad, B.; Haidar, R. Modeling the Effect of Reservoir Fluid Properties on Abundance of (H2S) Evolved from Oil Wells and Dissolved in Reservoir Fluids. In Recent Researches in Earth and Environmental Sciences; Springer Proceedings in Earth and Environmental Sciences; Mustafa, Y., Sadkhan, S., Zebari, S., Jacksi, K., Eds.; Springer: Cham, Switzerland, 2019. [Google Scholar] [CrossRef]
  13. Ismayilov, G.G.; Fataliyev, V.M.; Iskenderov, E.K. Investigating the impact of dissolved natural gas on the flow characteristics of multicomponent fluid in pipelines. Open Phys. 2019, 17, 206–213. [Google Scholar] [CrossRef]
  14. Makertich, D.; Samarrai, A. History of hydrocarbon exploration in the Kurdistan Region of Iraq. GeoArabia 2015, 20, 181–220. [Google Scholar] [CrossRef]
  15. Black oil PVT analysis, report reference F1713, DNO, Iraq.
  16. Jiang, S. Clay minerals from the perspective of oil and gas exploration. In Clay Minerals in Nature—Their Characterization, Modification and Application; IntechOpen: London, UK, 2012. [Google Scholar] [CrossRef]
  17. Hao, F.; Zou, H.Y.; Lu, Y.C. Mechanisms of shale gas storage: Implications for shale gas exploration in China. AAPG Bull. 2013, 97, 1325–1346. [Google Scholar] [CrossRef]
  18. Kuila, U.; Prasad, M. Specific surface area and poresize distribution in clays and shales. Geophys. Prospect. 2013, 61, 341–362. [Google Scholar] [CrossRef]
  19. Buday, T. The Regional Geology of Iraq; Volume 1: Stratigraphy and Paleogeography; Publications of Geological Survey of Iraq: Baghdad, Iraq, 1980; 445p. [Google Scholar]
  20. Tamar-Agha, M.Y.; Al-Aslami, M.; Facies, O.J. Depositional Environment and Cyclicity of the Fatha Formation in East Baghdad Oil Field, Iraq. Iraqi J. Sci. 2023, 56, 2939–2952. [Google Scholar]
  21. Cross, S.; Pettigrew, R.P.; Priddy, C.L.; Zuchuat, V.; Dodd, T.J.H.; Mitten, A.J.; Clarke, S.M. The sedimentological expression of transgression–regression cycles upon aeolian–marine margins. Depos. Rec. 2023, 9, 335–362. [Google Scholar] [CrossRef]
  22. Xiong, J.; Liu, X.; Liang, L.; Wei, X.; Xu, P. Investigation of the factors influencing methane adsorption on illite. Energy Sci. Eng. 2019, 7, 3317–3331. [Google Scholar] [CrossRef]
  23. Pozoa, M.; Pino, D.; Bessieres, D. Effect of thermal events on maturation and methane adsorption of Silurian black shales (Checa, Spain). Appl. Clay Sci. 2017, 136, 208–218. [Google Scholar] [CrossRef]
  24. Ji, L.M.; Ma, X.X.; Xia, Y.Q.; Qiu, J. Relationship between methane adsorption capacity of clay minerals and micropore volume. Nat. Gas Geosci. 2014, 25, 141–152. [Google Scholar]
  25. Salih, N.M.; Thannoun, R.G.; Bety, A.K. Hydrocarbon seepage detection by integrating remotely sensed and geochemical data: Scanning the lithological alteration. Arab. J. Geosci. 2023, 16, 153. [Google Scholar] [CrossRef]
  26. Mahmoud, M. Effect of Gas Adsorption on the Estimation of Gas in Place (GIP) in Conventional and Unconventional Reservoirs. Arab. J. Sci. Eng. 2019, 44, 6205–6214. [Google Scholar] [CrossRef]
  27. Salih, N.; Préat, A.; Gerdes, A.; Konhauser, K.; Proust, J.-N. Tracking the Origin and Evolution of Diagenetic Fluids of Upper Jurassic Carbonate Rocks in the Zagros Thrust Fold Belt, NE-Iraq. Water 2021, 13, 3284. [Google Scholar] [CrossRef]
  28. Qian, J.Z.; Luo, M.H. Effects of Moisture and Salinity on Methane Adsorption in Kerogen: A Molecular Simulation Study. Energy Fuel 2019, 33, 5368–5376. [Google Scholar] [CrossRef]
  29. Rashid, M.; Luo, M.; Ashraf, U.; Hussain, W.; Ali, N.; Rahman, N.; Hussain, S.; Martyushev, D.A.; Vo Thanh, H.; Anees, A. Reservoir Quality Prediction of Gas-Bearing Carbonate Sediments in the Qadirpur Field: Insights from Advanced Machine Learning Approaches of SOM and Cluster Analysis. Minerals 2023, 13, 29. [Google Scholar] [CrossRef]
  30. Hunt, J.M. Petroleum Geochemistry and Geology; W.H. Freeman and Company: New York, NY, USA, 1996; p. 332. [Google Scholar]
  31. Santos, R.G.; Loh, W.; Bannwart, A.C.; Trevisan, O.V. An overview of heavy oil properties and its recovery and transportation methods. Braz. J. Chem. Eng. 2019, 31, 571–590. [Google Scholar] [CrossRef]
  32. Demirbas, A.; Al-Ghamdi, K. Relationships between Specific Gravities and Higher Heating Values of Petroleum Components. J. Pet. Sci. Technol. 2015, 33, 732–740. [Google Scholar] [CrossRef]
  33. Shafiei, M.; Kazemzadeh, Y.; Martyushev, D.A.; Dai, Z.; Riazi, M. Effect of chemicals on the phase and viscosity behavior of water in oil emulsions. Sci. Rep. 2023, 13, 4100. [Google Scholar] [CrossRef]
  34. Zheng, Z.-Y.; Zuo, Y.-H.; Wen, H.-G.; Li, D.M.; Luo, Y.; Zhang, J.Z.; Yang, M.H.; Zeng, J.C. Natural gas characteristics and gas-source comparisons of the Lower Triassic Feixianguan Formation, Eastern Sichuan Basin, China. Pet. Sci. 2023, 20, 1458–1470. [Google Scholar] [CrossRef]
  35. Martyushev, D.A.; Chalova, P.O.; Davoodi, S.; Ashraf, U. Evaluation of facies heterogeneity in reef carbonate reservoirs: A case study from the oil field, Perm Krai, Central-Eastern Russia. Geoenergy Sci. Eng. 2023, 227, 211814. [Google Scholar] [CrossRef]
  36. Yang, C.-Y.; Li, M.-J.; Wang, T.-G.; Zhong, N.N.; Fang, R.H.; Wen, L. Texture development of mesophase in reservoir pyrobitumen and the temperature-pressure converting of the gas reservoir in the Chuanzhong Uplift, Southwestern China. Pet. Sci. 2023, 20, 721–732. [Google Scholar] [CrossRef]
  37. Raupov, I.R.; Milic, J. Improvement of operational efficiency of high water-cut oil wells. IOP Conf. Ser. Earth Environ. Sci. 2022, 1021, 012077. [Google Scholar] [CrossRef]
Jmse 11 01891 g001
Figure 1. General geological map showing the location of the studied Tawke area [14], the red and green zones are represented oil/gas fields.
Figure 1. General geological map showing the location of the studied Tawke area [14], the red and green zones are represented oil/gas fields.
Jmse 11 01891 g001
Jmse 11 01891 g002
Figure 2. Typical log package from Tawke oilfield, including GR, SP, and CAL.
Figure 2. Typical log package from Tawke oilfield, including GR, SP, and CAL.
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Figure 3. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas as a function of well depth.
Figure 3. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas as a function of well depth.
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Figure 4. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas as a function of reservoir temperature.
Figure 4. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas as a function of reservoir temperature.
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Figure 5. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas (i.e., Ch4, C2H6, C3H8) versus pressure of reservoir.
Figure 5. (a,c) Amount of evolved gas; (b,d) amount of dissolved gas (i.e., Ch4, C2H6, C3H8) versus pressure of reservoir.
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Figure 6. Amount of dissolved gas versus gas–oil ratio (a) CH4 in reservoir fluid; (b) C2H6 and C3H8 in reservoir fluid.
Figure 6. Amount of dissolved gas versus gas–oil ratio (a) CH4 in reservoir fluid; (b) C2H6 and C3H8 in reservoir fluid.
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Figure 7. (a,b) Amount of dissolved gas; (c)reservoir fluid density as a function °API.
Figure 7. (a,b) Amount of dissolved gas; (c)reservoir fluid density as a function °API.
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Figure 8. (a,b) Fluid viscosity at reservoir pressure, (c,d) at bubble-point pressure, and (e) as a function of well depth.
Figure 8. (a,b) Fluid viscosity at reservoir pressure, (c,d) at bubble-point pressure, and (e) as a function of well depth.
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Figure 9. Amount of dissolved gas versus coefficient of compressibility (a) CH4 in reservoir fluid; (b) C2H6 and C3H8 in reservoir fluid.
Figure 9. Amount of dissolved gas versus coefficient of compressibility (a) CH4 in reservoir fluid; (b) C2H6 and C3H8 in reservoir fluid.
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Figure 10. Amount of evolved gas versus gross heating value (a) CH4 evolved gas; (b) C2H6 and C3H8 evolved gas.
Figure 10. Amount of evolved gas versus gross heating value (a) CH4 evolved gas; (b) C2H6 and C3H8 evolved gas.
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Table 1. Reservoir properties and the estimated mathematical correlations.
Table 1. Reservoir properties and the estimated mathematical correlations.
No.Correlated ParametersMathematical ModelRegression Coefficient
xy
1Depth of samples (m)CH4 evolved (mole%)y = 94.22e − 7 × 10−4xR2 = 0.9717
CH4 dissolved (mole%)y = 5.5932e0.0024xR2 = 0.9848
C2H6 evolved (mole%)y = −0.808ln(x) + 5.0559R2 = 0.8235
C2H6 dissolved (mole%)y = 8 × 10−5x + 0.0615R2 = 0.9995
C3H8 evolved (mole%)y = −0.0023x + 1.4112R2 = 0.9519
C3H8 dissolved (mole%)y = 8 × 10−5x + 0.1565R2 = 0.9995
2Reservoir Temp.CH4 evolved (mole%)y = 135.26e−0.007xR2 = 0.6744
CH4 dissolved (mole%)y = 1.1509e0.0265xR2 = 0.9043
C2H6 evolved (mole%)y = −0.0261x + 2.9923R2 = 0.9536
C2H6 dissolved (mole%)y = 0.0008x + 0.0136R2 = 0.8369
C3H8 evolved (mole%)y = −0.0358x + 3.5502R2 = 0.9981
C3H8 dissolved (mole%)y = 0.0008x + 0.1086R2 = 0.8369
3Reservoir pressureCH4 evolved (mole%)y = 94.811e−4E−04xR2 = 0.7639
CH4 dissolved (mole%)y = 5.0536e0.0016xR2 = 0.9547
C2H6 evolved (mole%)y = 5 × 10−5x + 0.0591R2 = 0.9035
C2H6 dissolved (mole%)y = 5 × 10−5x + 0.0591R2 = 0.9035
C3H8 evolved (mole%)y = −0.0016x + 1.5319R2 = 0.9863
C3H8 dissolved (mole%)y = 5 × 10−5x + 0.1541R2 = 0.9035
4Gas–oil ratioCH4 dissolved (mole%)y = 8.707ln(x) − 26.868R2 = 0.9869
C2H6 dissolved (mole%)y = 0.0003x + 0.0605R2 = 0.9304
C3H8 dissolved (mole%)y = 0.0003x + 0.1555R2 = 0.9304
5Viscosity (cP) at reservoir pressureCH4 dissolved (mole%)y = −0.3836x + 18.55R2 = 0.9527
C2H6 dissolved (mole%)y = −0.001x + 0.104R2 = 0.885
C3H8 dissolved (mole%)y = −0.001x + 0.199R2 = 0.885
Viscosity (cP) at bubble-point pressureCH4 dissolved (mole%)y = −0.3466x + 17.766R2 = 0.9461
C2H6 dissolved (mole%)y = −0.0009x + 0.1018R2 = 0.8752
C3H8 dissolved (mole%)y = −0.0009x + 0.1968R2 = 0.8752
Depth (m)Viscosity (cP) at bubble point pressure y = −0.0714x + 39.463R2 = 0.860
6Coefficient of compressibility at reservoir pressure CH4 dissolved (mole%)y = 5 × 10+6x − 14.554R2 = 0.8892
C2H6 dissolved (mole%)y = 14,001x + 0.0146R2 = 0.798
C3H8 dissolved (mole%)y = 14,001x + 0.1096R2 = 0.798
7°APIFluid densityy = −0.0118x + 1.175R2 = 0.9981
°APICH4 dissolved (mole%)y = 0.0014e0.3803xR2 = 0.9773
C2H6 dissolved (mole%)y = 0.012x − 0.1985R2 = 0.9376
C3H8 dissolved (mole%)y = 0.012x − 0.1035R2 = 0.9376
8Gross heating valueCH4 evolved (mole%)y = 0.0016x + 10.64R2 = 0.9981
C2H6 evolved (mole%)y = 8 × 10−5x − 2.8784R2 = 0.7475
C3H8 evolved (mole%)y = 7 × 10−5x − 1.9633R2 = 0.8809
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Kamal, I.; Salih, N.M.; Martyushev, D.A. Correlations between Petroleum Reservoir Fluid Properties and Amount of Evolved and Dissolved Natural Gas: Case Study of Transgressive–Regressive-Sequence Sedimentary Rocks. J. Mar. Sci. Eng. 2023, 11, 1891. https://doi.org/10.3390/jmse11101891

AMA Style

Kamal I, Salih NM, Martyushev DA. Correlations between Petroleum Reservoir Fluid Properties and Amount of Evolved and Dissolved Natural Gas: Case Study of Transgressive–Regressive-Sequence Sedimentary Rocks. Journal of Marine Science and Engineering. 2023; 11(10):1891. https://doi.org/10.3390/jmse11101891

Chicago/Turabian Style

Kamal, Ibtisam, Namam M. Salih, and Dmitriy A. Martyushev. 2023. "Correlations between Petroleum Reservoir Fluid Properties and Amount of Evolved and Dissolved Natural Gas: Case Study of Transgressive–Regressive-Sequence Sedimentary Rocks" Journal of Marine Science and Engineering 11, no. 10: 1891. https://doi.org/10.3390/jmse11101891

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