Multiple linear regression approach for the vitrinite ...

Egyptian Journal of Petroleum xxx (2018) xxx–xxx

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Multiple linear regression approach for the vitrinite reflectance estimation from well logs: A case study in Sargelu and Naokelekan Formations – Shaikhan-2 Well, Shaikhan oil field, Iraq Hussein S. Hussein ⇑, Rzger A. Abdula Department of Petroleum Geosciences, Faculty of Science, Soran University

a r t i c l e

i n f o

Article history: Received 10 January 2018 Revised 28 February 2018 Accepted 19 March 2018 Available online xxxx Keywords: Shaikhan-2 Sonic log Resistivity log Vitrinite reflectance Multiple linear regression Sargelu Formation Naokelekan Formation

a b s t r a c t The sonic and resistivity logs for Sargelu and Naokelekan Formations in well Shaikhan-2 are utilized to predict vitrinite reflectance values. The precise prediction of vitrinite reflectance can be done based on well logs by applying multiple linear regressions method. This method is an extension from the regression analysis, which incorporates independent values to predict a dependent value. It is expected that both sonic and resistivity log readings in source rock that has reached oil window and hydrocarbons are cooked out of that, to be higher than source rock that is still in diagenesis stage and has not produced any oil and gas. Possible mechanisms to explain decreasing resistivity with increasing maturity include the existence of a conductive petroleum phase (pyrobitumen) and the increase in residual water salinity driven by water vapor solubility in the produced gas. The best matching between the vitrinite reflectance measured from the cutting samples and the vitrinite reflectance predicted from the log data in the well Shaikhan-2 has achieved. Ó 2018 Egyptian Petroleum Research Institute. 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/).

1. Introduction Shaikhan is strikingly one of the biggest Super Enormous oilfields found in the final 50 a long time. It was pronounced a commercial disclosure in mid-2012 taking after a five-well examination program. At first free gauges put the net oil-in-place (OIP) volume at 13.7 billion barrels possibly making it one of the biggest oilfields found in Iraqi Kurdistan [1]. Shaikhan’s oil is heavy: when refined, it evokes great quantity ‘‘bottom-of-the-barrel” items such as bitumen and tar. That implies it tends to exchange at a markdown to lighter crudes. Acrid oil such as Shaikhan’s, with its extraordinary sulfur content requires distinct treatment, since sulfur can erode refining and preparing gear [2]. The study of vitrinite reflectance (or Ro) is a key method for strategy for recognizing the most extreme temperature history of deposits in sedimentary basins and maturation assessment of source rocks [3]. Conferring to a literature review [4–6], temperature and time are deliberated as the key factors manipulating vitrinite reflectance escalation according to first-order kinetics [7].

Peer review under responsibility of Egyptian Petroleum Research Institute. ⇑ Corresponding author. E-mail address: [email protected] (H.S. Hussein).

The Sargelu and Naokelekan Formations’ organic matter from Shaikhan-2 (Sh-2) in northern Iraq is a mixture of oil and gas prone and thermally matures according to Tmax values that obtained by Rock-Eval pyrolysis [8]. This study tries to evaluate the thermal maturity of Sargelu and Naokelekan Formation’s organic matter in well Sh-2. For this reason, the sonic interval transit time (DT) and true resistivity (Rt) logs in open hole were used. The Sh-2 Well is located within Shaikhan Block. The Shaikhan block is located around 85 km northwest of Erbil Governorate covering an area of 283 km2 and is one of the onshore developments. Sh-2 Well was drilled nine kilometers southeast of the Shaikan-1 Discovery Well with coordinates 36° 460 22.100 N and 43° 260 42.900 E (Fig. 1). 2. Methodology The basic concept of this study comes from the theory that ‘‘well log data respond to the thermal maturation of organic matter”. The theory is a fundamental to discover a way to estimate vitrinite reflectance from well logs data. Expulsion of hydrocarbons out of a mature source rock will affect both DT and Rt log readings (Fig. 2). It is expected that both DT and Rt log readings in source rock that has reached oil window and hydrocarbons are cooked out of that, to be higher than source rock that is still in diagenesis

https://doi.org/10.1016/j.ejpe.2018.03.013 1110-0621/Ó 2018 Egyptian Petroleum Research Institute. 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/).

Please cite this article in press as: H.S. Hussein, R.A. Abdula, Multiple linear regression approach for the vitrinite reflectance estimation from well logs: A case study in Sargelu and Naokelekan Formations – Shaikhan-2 Well, Shaikhan oil field, Iraq, Egypt. J. Petrol. (2018), https://doi.org/10.1016/j. ejpe.2018.03.013

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H.S. Hussein, R.A. Abdula / Egyptian Journal of Petroleum xxx (2018) xxx–xxx

Fig. 1. Index map of Iraqi Kurdistan showing the locations of the studied well [1].

Fig. 2. Sonic (DT) and resistivity (Rt) logs for Sargelu and Naokelekan formations in well Shaikhan-2.

stage and has not produced any oil and gas. This is due to the physical fundamental that hydrocarbons increase the sonic transit time and cause resistance against electrical currents. The more precise prediction of vitrinite reflectance can be done based on well logs by applying multiple linear regressions method.

This method is an extension from the regression analysis, which incorporates independent values to predict a dependent value. The log vitrinite reflectance is dependent value and independent value is considered as well log data. In this study, the DT and Rt log data were utilized as independent value to predict the dependent vitrinite reflectance values. In multi linear regression, the vitrinite reflectance is based on the facts that the Rt has a negative and interval transit time has a positive relation with vitrinite reflectance or level of maturation. The range of vitrinite reflectance for the well was defined already from rock sample data as shown in Red dotted color (Fig. 3-upper right hand). The calculated vitrinite reflectance value from the rock sample is used as the anchor point for rock typing. The value of log is selected at absolutely the same depth as the rock samples (Table 1). A multiple regression assay is then performed to establish an accurate mathematical model for predicting vitrinite reflectance using the log data (DT and Rt) (Table 1). Sonic and resistivity log are two strong parameters relating to the thermal maturation of source rocks, therefore suitable to determine vitrinite reflectance. The gamma ray log is not included in this approach (Multiple Linear Regression) because it is more reliable to determine organic matter richness than maturity. Gamma ray is utilized to calculate shale volume and mostly the amount of shale volume is corresponds to the presence of organic matter (Fig. 4). The vitrinite reflectance values that obtained from DT and Rt log readings were correlated with vitrinite reflectance values that obtained mathematically from Tmax values. To interpret the geochemical data that obtained from Rock-Eval pyrolysis, the principles of Petter and Cassa [9] were applied. Eq. (2) shows the final model.


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Fig. 3. Left hand is vitrinite reflectance obtained from sonic and resistivity logs for the whole intervals of the studied formations (blue) and their comparative values obtained from rock sample (red), upper right hand is calibrated and predicted vitrinite reflectance of log for the same depth of vitrinite reflectance from rock samples (blue) and from multiple linear regression (red), and the lower right hand shows the comparison of Ro from log and from rock samples relationship.

Table 1 Shared values in multiple linear regressions to have built the mathematical model (Eq. (2)) and shows the vitrinite reflectance from log data by using this model for the same available vitrinite reflectance of rock sample. Depth (m)

Ro (Rock sample)

Rt

DT

Intercept

RT coefficient

DT coefficient

Ro (Log)

1736 1741 1746 1751 1756 1761 1766

0.544 0.634 0.562 0.508 0.508 0.544 0.562

8.000 13.000 15.000 18.000 19.000 18.000 18.000

51.000 68.000 56.000 53.000 53.000 56.000 61.000

0.250 0.250 0.250 0.250 0.250 0.250 0.250

0.0045 0.0045 0.0045 0.0045 0.0045 0.0045 0.0045

0.0065 0.0065 0.0065 0.0065 0.0065 0.0065 0.0065

0.546 0.634 0.547 0.514 0.509 0.533 0.566


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Fig. 4. Gamma-ray log data (left), Shale Volume% (center), and Lithological column from cutting sample (right) for Sargelu and Naokelekan Formations [1] in well Shaikhan-2.

3. Geological setting The northern and northeastern parts of Iraq are a part of an Alpine mountain belt. This belt has a northwest–southeast trend in northeastern Iraq and east–west direction in northern Iraq. The Sh-2 Well is located in the High Folded Zone in northern Iraq. It should be noted the rocks on the surface at this well location are latest Eocene in age [10].

The Sargelu and Naokelekan Formations are combined together here due to their similarity in lithology and petrophysical properties. The boundary between Sargelu and Naokelekan Formations can be sited within a thin-bedded limestone sequence. The absence of chert and abundant Bositra buchi sp. are indicators to differentiate Naokelekan Formation from the underlying Sargelu Formation. Likewise, the remarkably kerogenous and characteristically slanted nature of the bed is recognizable from Sargelu Formation [5,11]. In


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H.S. Hussein, R.A. Abdula / Egyptian Journal of Petroleum xxx (2018) xxx–xxx Table 2 Rock-Eval pyrolysis data for Sargelu and Naokelekan Formations’ organic matter in well Shaikhan-2 [8]. Sample No.

Depth (m)

TOC (wt%)

S1 (mg HC/g TOC)

S2 (mg HC/g TOC)

S3 (mg CO2/g TOC)

Tmax (°C)

PI

HI (mg HC/g TOC)

OI (mg HC/g TOC)

PCI (mg HC/g TOC)

S1/TOC

Ro%

S2/S3

1 2 3 4 5 6 7

1736 1741 1746 1751 1756 1761 1766

1.68 1.38 1.32 1.58 1.17 1.49 1.55

1.41 1.00 1.30 1.17 1.10 1.30 1.46

6.21 5.39 5.35 4.57 4.76 6.55 7.16

1.56 1.47 1.75 1.88 1.64 1.66 1.61

428 433 429 426 426 428 429

0.18 0.16 0.20 0.20 0.19 0.17 0.17

370 391 405 289 407 440 462

93 107 133 119 140 111 104

6.32 5.30 5.52 4.76 4.86 6.52 7.15

0.84 0.72 0.98 0.74 0.94 0.87 0.94

0.54 0.63 0.56 0.51 0.51 0.54 0.56

3.98 3.67 3.06 2.43 2.90 3.95 4.45

TOC – total organic carbon. S1 – total free hydrocarbons (from S1 peaks). S2 – amount of remaining hydrocarbon or amount of hydrocarbon obtained by heating during pyrolysis (from S2 peaks). S3 – amount of carbon dioxide (CO2) released through heating organic matter (from S3 peaks). Tmax – highest temperature for generating a maximum amount of hydrocarbon during pyrolysis. PI – production index. HI – hydrogen index. OI – oxygen index. PCI – pyrolyzable carbon index. Ro – vitrinite reflectance.

Fig. 5. Oxygen index versus hydrogen index to determine the type of kerogen for organic matter from Sargelu and Naokelekan Formations in well Shaikhan-2 [17].


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Iraq, these formations occur on the surface in several localities including the following: (1) Northern Thrust Zone; (2) High Folded, Balambo–Tanjero Tectonic Zone; and (3) within the Qulqula– Khwakurk Tectonic Zone [10,12]. In Sh-2 Well (Fig. 4), Sargelu and Naokelekan Formations are underlain by Alan Formation. Regularly, the lower contact is rather clear cut and is defined by the last occurrence of anhydrite at the top of the Alan Formation and it is conformable and gradational [13]. In the same well, they are overlain by Barsarin Formation. The upper boundary can be found within a basically analogous thin bedded limestone sequence below the stromatolitic limestone bed [11]. The thickness of both formations is 45 m. The lithological composition of both formations is very consistent [12]. It is comprised of limestone, shale, and chert (Fig. 4). The limestone is thin-bedded, bituminous, dolomitized, dark brown, brown, yellowish brown, light grey, firm to slightly hard, subblocky micritic, occasionally microcrystalline, poor porosity, argillaceous in

places. The shale is predominately dark brown papery, commonly black occasionally grey, firm to slightly hard, platy occasionally subblocky, weakly fissile, calcareous in places, silty texture with traces of anhydrite. They include the succession of thin bedded, calcareous-argillaceous sediments and streaks of thin black chert. The oilfield contains successions (Fig. 4) of limestone reservoirs stacked upon each other. These reservoirs include exceptionally long period of geological time, from the Triassic, which began some 248 million years ago to the Cretaceous, which ended some 65 million years ago to [1].

4. Results Sargelu and Naokelekan Formations’ organic matter were screened based on S1/TOC to differentiate indigenous from non-indigenous. Both formations contain 1.17–1.68 (average

Fig. 6. Measured vitrinite reflectance versus hydrogen index to determine the type of kerogen for organic matter from Sargelu and Naokelekan Formations in well Shaikhan-2 [18].



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Fig. 7. Maturity (measured vitrinite reflectance in oil, %Ro) versus production index (PI) for samples from Sargelu and Naokelekan Formations in studied well, Shaikhan-2 shows that organic matters are mature [19].

1.45) total organic carbon (TOC) wt%. The organic matters’ hydrogen index (HI) and oxygen index (OI) ranges are 289–462 (average 395) and 93–140 (average 115) mg HC/g TOC, respectively. The Tmax values are between 426 and 433 (average 428) °C (Table 2). The vitrinite reflectance (Ro) values obtained from DT and Rt logs for organic matters have a range of 0.44–0.71 (Table 1). This range correlates positively with vitrinite reflectance values that obtained mathematically from Tmax values which are 0.51–0.63 (Table 2) for the same organic matters in the same well (Fig. 3). The vitrinite reflectance values on the (Table 2) were obtained mathematically by using the Jarvie’s [14] equation which is:

Ro ðcalculatedÞ¼ð0:018Þ ðTmax Þ 7:16

ð1Þ

This equation is based on the direct proportional relationship between Tmax and vitrinite reflectance. Jarvie’s [14] equation was used to evaluate the proposed method for determining vitrinite reflectance from well logs. The shale volume determined from gamma-ray log (Fig. 4). The figure shows a strong relation and positive correlation between the amount of shale from rock sample (lithological column) and shale volume from the gamma ray. The lithological column shows the Naokelekan Formation contains mostly dolomite and shale and Sargelu Formation comprises of marl, organic rich limestone and shale. The best matching between the vitrinite reflectance measured from the cutting samples and the vitrinite reflectance predicted from the log data in the well Sh-2 has achieved using the Eq. (2),

Ro ðpredictedÞ ¼ 0:25 0:0045Rt þ 0:0065DT

ð2Þ

This equation has driven from the log data (DT and Rt) as independent to find out the dependent value (log derived vitrinite reflectance) from rock sample vitrinite reflectance, which is derived from Tmax (Eq. (1)). All values that shared to build this model (Eq. (2)) in multiple linear regressions are shown in Table 1.

Finally, it has used to predict vitrinite reflectance for the whole intervals of the studied formations (Fig. 3).

5. Discussion Sargelu and Naokelekan Formations’ organic matter are indigenous based on S1/TOC values, which are less than 1.5 [15]. The TOC wt% of Sargelu and Naokelekan Formations ranges from 1.17 to 1.68. The high TOC wt% content is not enough to determine the quality of organic matter. The high carbon richness along with high hydrogen contents is required for any source rock to generate hydrocarbons and consequently to be considered a good source rock [16]. Thus, both formations considered a good source rocks based on their TOC contents and their hydrogen indices. All samples have hydrogen index greater than 300 mg HC/g TOC except the one that collected from the depth 1685–1690 m has 289 mg HC/g TOC. Therefore, organic matters belong to type II kerogen except one sample that was collected from the previous mentioned depth (Figs. 5 and 6). The vitrinite reflectance values obtained from DT and Rt logs were calibrated with vitrinite reflectance values that were obtained mathematically from Tmax values (Fig. 3). The vitrinite reflectance values from DT and Rt logs are 0.44–0.71 (average 0.57) and from mathematically obtained from Tmax are 0.51–0.63 (average 0.55) (Table 1). These values indicate that organic matters are within oil window (Fig. 7). It appears that vitrinite reflectance increases with increasing shale volume. This may be related to sticking and consequently remaining heavy compounds within shale due to low permeability (Fig. 3). The organic matters belong to type II and mixture of type II and III with different hydrogen indices. The compounds with lower hydrogen and higher oxygen contents appear to have higher vitrinite reflectance values and vice versa. Possible mechanisms to explain decreasing resistivity with increasing maturity include the existence of a conductive petro-


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leum phase (pyrobitumen) and the increase in residual water salinity driven by water vapor solubility in the produced gas. 6. Conclusions The following can be concluded from this study: – Sargelu and Naokelekan Formations are representing good source rocks according to their TOC wt% contents and hydrogen indices; – The organic matters belong to type II and II/III kerogen; – The organic matters are mature and within early oil window; – The DT and Rt logs can be used to predict vitrinite reflectance; and – Good match exists between vitrinite reflectance values obtained from logs (DT and Rt) and from rock samples.

Acknowledgments The authors are grateful to Ministry of Natural Resources in Iraqi Kurdistan for providing the well logs and cutting samples. The author thanks the Kurdistan Institution for Strategic Studies and Scientific Research (KISSR) in Sulaimani, Iraqi Kurdistan especially Diar A. Saeed for his technical support. References [1] Gulf Keystone Petroleum Ltd., Investor presentation: www.gulfkeystone.com. http://www.gulfkeystone.com/media/15312/gkpinvestorpresentation1213 october2011.pdf, 2011 (accessed on December 23, 2017). [2] G. Chazan, Heavy oil/Shaikhan sour throws up mix of production headaches. https://www.ft.com/content/67f62576-2f2f-11e2-b88b-00144feabdc0, 2012 (accessed on December 22, 2017). [3] W.G. Dow, Kerogen studies and geological interpretation, J. Geochem. Explor. 7 (1977) 79–99.

[4] B. Durand, B. Alpern, J.L. Pittion, B. Pradier, Reflectance of vitrinite as a control of thermal history of sediments, in: J. Burrus (Ed.), Thermal Modelling in Sedimentary Basins, Technip, Paris, 1986, pp. 441–474. [5] D.G. Murchison, A.C. Cook, A.C. Raymond, Optical properties of organic matter in relation to thermal gradients and structural deformation, Philos. Trans. R. Soc. London, A 315 (1985) 157–486. [6] B.P. Tissot, D.H. Welte, in: Petroleum Formation and Occurrence, SpringerVerlag, Berlin, 1984, p. 699. [7] A.K. Burnham, J.J. Sweeney, A chemical kinetic model of vitrinite maturation and reflectance, Geochim. Cosmochim. Acta 53 (1989) 2649–2657. [8] R.A. Abdula, Source rock assessment of Naokelekan Formation in Iraqi Kurdistan, J. Zankoi Sulaimani 19 (1) (2017) 103–124. [9] K.E. Peters, M.R. Cassa, Applied source rock geochemistry, chapter 5, in: L.B. Magoon, W.G. Dow (Eds.), The Petroleum System—From Source to Trap: AAPG Memoir 60, 1994, pp. 93–120. [10] S.Z. Jassim, T. Buday, Late Toarcian-Early Tithonian (Mid-Late Jurassic) Megasequence AP7, chapter 10, in: S.Z. Jassim, J.C. Goff (Eds.), Geology of Iraq, first ed., Prague and Moravian Museum, Brno, Czech Republic, 2006, pp. 117–123. [11] R.A. Abdula, Stratigraphy and lithology of Naokelekan Formation in Iraqi Kurdistan-review, Int. J. Eng. Sci. 5 (8) (2016) 2319–11805. [12] T. Buday, The regional geology of Iraq, in: Stratigraphy and Paleogeography, Dar Al-Kutub Publishing House, University of Mosul, Mosul, Iraq, 1980, p. 445. [13] R.A. Abdula, S.M. Balaky, M.S. Nurmohamadi, M. Piroui, Microfacies analysis and depositional environment of the Sargelu Formation (Middle Jurassic) from Kurdistan Region, northern Iraq, Donnish J. Geol. Min. Res. 1 (1) (2015) 001– 026. [14] D.M. Jarvie, F. Mbatau, A. Maende, D. Ngenoh, D.A. Wavrek, Petroleum systems in northwest Kenya. Presented at the Annual Meeting of the American Association of Petroleum Geologists, Denver, CO, 2001. [15] J.M. Hunt, in: Petroleum Geochemistry and Geology, second ed., W. H. Freeman, and Company, New York, 1996, p. 743. [16] H. Dembicki Jr, Three common source rock evaluation errors made by geologists during prospect or play appraisals, AAPG Bull. 93 (3) (2009) 341– 356. [17] J. Espitalié, J.L. Laporte, M. Madec, F. Marquis, P. Leplat, J. Paulet, A. Boutefeu, Rapid method for source rocks characterization and for determination of petroleum potential and degree of evolution, Revue De L’institut Français Du Pétrole (IFP) 32 (1) (1977) 23–42. [18] J. Espitalié, G. Deroo, F. Marquis, Rock-Eval pyrolysis and its applications, Revue De L’institut Français Du Pétrole (IFP) 40 (5) (1985) 563–579. [19] K.A.K. Ghori, Modeling the hydrocarbon generative history of the Officer Basin, Western Aust.: Pet. Explor. Soc. Aust. (PESA) J. 29 (2002) 29–43.


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