Reservoir Characterization and Rock Typing of Carbonate Reservoir in the Southeast of Iraq

Abstract


Introduction
Rock typing and reservoir characterization are significant tools in prediction and performance of reservoirs and in understanding reservoir architecture (Al-Jawad et al., 2020;Al-Dolaimy et al., 2021) The hydrocarbon storage capacity of a reservoir is determined by its porosity, but deliverability is determined by its permeability (Ismail and Al-Najam 2019).The purpose of the reservoir characterization method is to recognize reservoir quality (Shedid, 2018).The flow unit approach has been widely employed for pore-scale rock type classification based on flow attributes depending on geological factors and the physics of the flow (AbdulMajeed and Alhaleem, 2020;Mahmood and Al-Fatlawi, 2021).These flow units reflect reservoir compartments with comparable petrophysical and geological characteristics, but they are unique from other reservoir divisions in terms of fluid flow(Al-Jawad and Saleh 2020).
Rock typing, by definition, is the classification of reservoir rocks into different units.These units were deposited in similar environments and went through similar diagenetic processes (Awadeesian et al., 2018).For each rock type, this results in a distinct porosity-permeability relationship, a similar capillary pressure profile, and the same water saturation for a given height above the free water level.(Bhatti, 2020).
A rock's hydraulic properties are determined by its pore geometry (AlJuboori et al., 2020).Texture and mineralogy play a significant influence in this process, as do their quantity and placement in relation to the pore throat (i.e., grain size, grain shape and packing) (Al-Fatlawi, 2018).The presence of separate rock units with comparable pore throat features is typically indicated by different combinations of these geological traits.Identifying the pore throat features is necessary for accurately zoning reservoirs into units with similar hydraulic parameters (Amaefule, 1993).
Five wells from east south of Iraq have been selected as they were consistently spread across the Mishrif formation to determine the reservoir's characteristics and rock type.The field is one of Iraq's most major southern east oil fields.It is in Dhi Qar city.The field's 34 km length and 17 km width suggest the presence of unfaulted subsurface fold structure with a general northwest-southeast trend (Jreou, 2013).The shallowest hydrocarbon-bearing formation in Iraq's X field is the Mishrif reservoir.Fine to coarse bioclastic limestones are characterized by a shallow depositional domain (Khalaf, 2009).
The average thickness is about 180 m, in X field, the formation can be subdivided into two intervals, separated by a layer 10-12 m thick of shale with carbonate intercalations.Mishrif Formation is oil bearing only in the lower section, which has an average thickness of about 100 m. (Amna, 2006 andJreou, 2013).Fig. 1 represents the stratigraphic column of the Mishrif Formation in XX field.(Jreou, 2013)

Flow Zone Indicator (FZI) and Rock Quality Index (RQI)
The relationship of core analysis data to the Rock Quality Index (RQI) depends on its indication of flow zone is deemed one of the best techniques for locating and classifying flow units (Soleymanzadeh et al., 2019).
FZI is calculated using core data from cored wells and usually applied to uncored wells based on correlations of log attributes (Al-Qattan and Al Mohammed, 2017).
This specific factor, known as the indicator flow zone (FZI), is used to discover the geological parameters that influence the fluid flow, particularly when geological features based on variation in diameters of pore-throats, which affect permeability are considered (Amaefule, 1993): Where: RQI: is the reservoir quality index (μicron), FZI: is a quality of reservoir index function and void ratio (μicron), Øeff: is the effective porosity (fraction), and Øz : is a normalized of porosity (volume of pore -to volume ratio of grain) (fraction).

Winland Method
Pore throat size and porosity were investigated by Winland using mercury injection experimental studies on numerous sandstone and carbonate rock samples.The best correlation analysis (R2) was found to be associated with a mercury saturation level of 35%.In the case of 35% mercury saturation, the diameter of the pore throat is r 35 (Soleymanzadeh et al., 2019).
Determining pore throat size (R35) form core porosity and permeability for the reservoir units provides the best basis of defining reservoir flow units (Al-Jawad, 2014).An interval of rock with similar fluid flow and average pore throat radii is a petrophysical rock type (PRT) technique (Opuwari et al., 2021).The following is the Winland correlation: log R35 = 0.732 + 0.588log k − 0.864log ϕ (4) where R35 is in µicron, k is the uncorrected permeability of air in mD.ϕ is porosity in %.
The radius of the pore throat can be identified as Table 1, Fig. 2.

Lucia Method
Rock permeability and saturation are controlled by the porous structure of the rock, and the Lucia classification classifies the spatial distribution of pore sizes within that rock.Carbonate rock textiles can be linked to pore-size distribution if the pore space is classified as either interparticle, separate-vug, or touching-vug, depending on the type of pore (Lucia, 2007).(Pittman, 1992) Lucia's Petrophysical Rock Classification employs laboratory measures of porosity and permeability to connect pore size distribution to the number of rock fabrics in a sample (Bhatti, 2020).Rock fabric number is a formula (5) provided by Lucia (2007) (RFN) (Fig. 3).

Cluster Analysis
Cluster analysis was used to categorize well log data based on degree of similarity or dissimilarity across groups in order to develop rock type log using an internally homogeneous and externally isolated approach (Al-Jafar and Al-Jaberi, 2019).
An initial estimated mean value for each cluster is assumed for each input loge data set, and then the sum of squares difference between data points and the cluster mean value is minimized inside each cluster using a K-mean statistical approach (Anon 2021).
The raw and interpreted log data for shale volume (Vsh), bulk density (RHOB), effective porosity (PHIE), and water saturation (Sw) for the five studied wells were used as input data in cluster analysis by using IP 2018 program.

Flow Zone Indicator (FZI) and Rock Quality Index(RQI)
All of the wells' RQI versus FZI plot functions were created for each reservoir unit using the equations in Eqs. 1, 2, and 3. Fig. 4 represent a plot for Porosity versus Permeability and Fig. 5) reflect reservoir quality index (RQI) versus the logarithm of the normalized porosity (ØZ); for various values of the flow zone indicator (FZI).There are four distinct rock types and groups in the Mishrif formation; the pore throat of all points with the same (FZI) line is the same.Whereas, the first category (FZI-1) (Mudstone Microfacies) reflects poor reservoir quality (with a permeability of less than 0.1 Md), the second group represents a fair rate of the reservoir (FZI-2) (Wackestone-Mudstone Microfacies) with permeability range 0.1-10 md, FZI-3 is characterized by permeability more than 10 md (Packstone-Wackestone Microfacies) in the third group, and its permeability is greater than 100 md in the fourth group (FZI-4) (Grainstone-Packstone Microfacies) and the quality of the reservoir is excellent.

Winland Method
Five categories of PRT or rock types For the Mishrif Reservoir were identified by the Winland technique with equal (R35) pore throat sizes and similar reservoirs characterization.Table 2 summarizes the variability associated with petrophysical properties associated with each rock type, while Figs. 6. a and b indicate the application of the Winland method for studied wells.More than 10 More than 100 Megapores

Lucia Method
Three rock types are identified by the Lucia method depending on rock fabric number the first class is Grain-dominated Fabrics grainstone, with Rfn (0-1.5); this class is a very good representation in the formation with a high value of permeability; the second group contains grainstone and packstone, with RFn (1.5-2.5) which reflected suitable rock quality type of Mishrif Formation.The third group is Muddominated Fabrics containing packstone, wackestone RFn (2.5-3.5) and mudstone Rfn more than 3.5 , which reflect intermediate to bad rock quality type, Fig. 7 indicate the Lucia application on studied wells.

Cluster Analysis
The randomness result, as shown in Fig. 8, which was used as input data in cluster analysis by using the IP program, resulted in four cluster types from twenty assumed clusters, as represented in Dendrogram (Fig. 9), which has identified four groups belong to Mishrif rock typing.
Fig. 10 illustrates the cluster multi-curve cross plot of cluster analysis for the studied wells.The rock type details of the Mishrif Formation.Four petrophysical rock-type groups have been identified as follows: • Petrophysical Rock Type 4 (Green color) this rock type (PRT_4) has characterize by very good petrophysical properties with porosity ranging from 18 to 23%, and permeability range from100 mD to 1000 mD, with low water saturation content (20%-35%).• Petrophysical Rock Type 3 (Blue color) this type represent good to intermediate petrophysical properties are observed, with porosity ranging from 10 to 18% and permeability from 10 to 100 mD and considered high water saturation zone (more than 45 %).• Petrophysical Rock Type_2 (Red color) considers the fair properties belong to the average porosity is 11%, permeability range 1-10 md and high-water saturation more than 70%.
• Petrophysical Rock Type 1 (Yellow color) This PRT consisted of high a shale volume fraction.The petrophysical properties porosity, and permeability are less than 1 with high-water saturation (90% -100%).It appears as cap rock of mishrif formation and as shale separated layer in the middle part.Table 3 represents the final rock type statistical results using cluster analysis technique and Figs.10, 11, 12, 13, 14 illustrated cluster analysis results for all wells studied.

Conclusions
This study focused on determining rock type and flow unit in carbonate reservoir, Mishrif Formation in southeast Iraq was chosen.There are four distinct groups by combining the three approaches (FZI, Winland r35, Lucia) using core analysis and cluster technique based on log data (Grainstone-Packstone, Packstone-Wackestone, Wackestone-mudstone and Mudstone) as described below: • Rock type-1 (PRT-4) represents the best petrophysical properties.Rocks which mainly contain Grainstone-Packstone, belonging to class 2 of Lucia's Petrophysical classification, the pore throat size is the best with Winland r 35 more significant than 10 μm and FZI more than 4 μm.• Rock type-2 (PRT-3 ranks as good to intermediate reservoir quality rock, which is mainly composed of packstone.The calculated Winland r35 pore throat size values range between 2.5 and 6 μm, FZI between 2 and 3 μm.• Rock Type-3 (PRT-2) considered as fair properties, which is mainly composed of wackestonemudstone belong to Class 3 of Lucia classification, the pore throat size range (0.29 -0.83) micron and the FZI about 1 micron.• Rock Type-4 (PRT-1) this rock is consisted of a large volume of shale that appears as cap rock of the Mishrif Formation and as shale separated layer in the middle part.

Table 2 .
Petrophysical properties by Winland Method

Table 3 .
Cluster analysis results for each rock type