Estimation of Porosity and Permeability by using Conventional Logs and NMR Log in Mishrif Formation/Buzurgan Oil Field

Permeability and porosity values regarded as important fundamentals in the petroleum studies and researches especially for the interests in the reservoir topics, many methods and tools were founded for this purpose from time to time. The modern log technology one of this tools but consumes more time and financial possibilities in addition to the experts, such as Nuclear Magnetic Resonance Tools which considered one of the unconventional logs, so that, for this it was necessary to find a method to get the permeability and porosity values for the NMR log by using the conventional logs, note that it has been confirmed the modern studies the high accuracy and reliability for the NMR permeability and NMR porosity. Because the importance of this values , this study deals with the possibility of get these values from the conventional logs with these from NMR log, because of ease dealing with conventional logs and ease of getting it. After making the data analyses and processing this study results that led to putting many transformation formulas which give high correlations to high accuracy applying for this values in the researching and applying aspects and relating with reservoir prediction and modeling which connecting with drilling and producing works. The carbonate Mishrif Fm. In the Buzurgan oil field was selected to achieve this study by chose four oil production wells(Bu-40, Bu-51, Bu-52) in the south and north domes, in the future facilitate the prediction ways for any well has been logged by the open hole logs.


Introduction
Nuclear magnetic resonance (NMR) logging tools have captured the interest particularly for the petroleum researchers [1]. The principle of NMR logging by the use of the large permanent magnets to create a strong static magnetic field to align the spin axes of protons in a preferred orientation and polarization, which consumes time called polarization time T1. The second main NMR measurement known as the transverse relaxation time, or T2, which is a composite of a number of individual fluid decays in a formation [6]. A small pore has a rapid relaxation time and a large pore provides slower relaxation. For bulk crude oils, the T2 distribution reflects the oil composition molecularly [4]. The long T2 distribution in the crude oil corresponds to effect of the molecules that mobile, while the short T2 is associated with signals from larger molecules, the viscosities of the macroscopic oil can be computed by using the crude oil No.24-(9) 2019 Journal of Petroleum Research & Studies (JPR&S) E77 of the T2 logarithmic mean distributions. The diffusion (D) considered as the protons move through the gradient of the applied field. Molecular diffusion is the thermal motion for the molecules moved randomly; a molecule have constant diffusion limiting the mean square distance that the molecule will move per unit time, for the gas and water is described by a single molecular diffusion constant [7].

Open Hole Analyses (OHA)
Log Quality Control: By using PETROLOG program, the data was sampled at 0.1m.
Before the petro-physical analysis the data was properly checked. It was noted that it does not require any editing as the data is of good quality.
Environmental corrections: Environmental corrections have been applied to the data using standard Weatherford charts for compact tools from the field and during the analysis the Compact Tornado Chart used for deriving the R T (formation resistivity).
And R xo (flushed zone resistivity). Ø N (neutron porosity).was corrected for pressure, based on the mud density.
Porosity determination: To determine Ø T (total porosity)and Ø E (effective porosity )the model of complex lithology was used, Ø S (sonic porosity): The D-N X-plot was used to compute ρ m (matrix density) after correcting ρ b (bulk density) and Ø N for V CLAY ( clay volume) and hydrocarbon corrections. Where the ρ b was not good D T35b (compensated sonic log) and Ø N were used.
Uncertainty Analysis: The uncertainty values should preferably be entered following a full Monte Carlo analysis (is a mathematical modeling technique that allows you to see all possible outcomes and assess risk to make data -driven E78 decisions) and using a fix cut-off for all parameters, but for this wells, it was use default value provided on the software with industry general concept of uncertainty associated with each logging tools.
Permeability Determination: Multiple linear regression [6] widely used as a statistical approach. The technique of linear regression were familiar to establish geological variables predictors, this ways were useful to predicted the means value, fast in computing, are majority existed in packages of the statistical software dependency. The prediction by using one or more than one input variables, a relationship of a straight-line between log(k) and Ø finds the computation for log(k) by Eq.

NMR Analyses (NMRA)
Porosity existence: The micro-porosity related to the clay which have water, from an NMR view, show same a solid because water in the micro-pores give a very rapid T2, consequently, this water is difficult to be noticed [9]. Porosity determination from NMR, The short decay time reflects a small pore size while the long decay time represented the coarse pore size meaning every bin considered a pore sizes ranges at the smallest 0 m sec and ending by the coarsest 512 m sec [5]. The distribution of the pore size is a relative measure of the S/V ratio of the pores.
Permeability estimation: The free-fluid model (Coates model) may be used in the reservoirs that saturated with water or hydrocarbon, while the mean-T2 model (SDR model) may be used in the reservoirs that saturated with water [8]. In the Coates model, the pore-size value used from T2cutoff, which resulted the ratio of Free Fluid Index(FBI) to the Bulk Volume Index(BVI) while in the SDR model, the pore-size value used from the T2 geometric mean(T 2LM ) [9]. The Timur-Coates (TC) equation applying Bulk Volume of Irreducible water and Free Fluid Inde, where C is constant depending on No.24-(9) 2019 Journal of Petroleum Research & Studies (JPR&S) E79 formation, K is permeability and Ø is porosity [3]. As in equations (6 and 7): Results and Discussion:

Conventional and NMR logs results Correlations:
Available conventional wire lines logs for this work including DT (Sonic log), ρb, Ø N (Neotron log), R T (Resistivity log), PEF (Photoelectric factor), GR (Gamma Ray), and Caliper. Caliper log was firstly used to identify an undesirable whole intervals. The intervals have wicked hole must be removed to avoid the non-good reads. PEF is a litho-log which determines composition of reservoir rocks. NMR log is having no lithology dependency. Therefore that, t h e Photoelectric was not important to use as an input data. GR considered as a shale indicator. In this study, four conventional well logs including DT, ρb, Ø N , and RT were chosen as input data. These are known appropriate input logs having logical relationship with outputs, because the first three logs are porosity logs and the last one is attributed to fluid flow pass (tortuosity) [2].
Figures in appendix one, show the logical dependency of chosen traditional wire lines information with nuclear magnetic resonance log parameters using the concept of correlation coefficient. In all wells there is a strong correlations (colored with blue), moderate correlations (colored with pink) and weak correlations (colored with red) as illustrated in Table (1). In the wells Bu-40 the strong correlations was between: -Logarithmic mean of conventional permeability (LogKcon.) versus conventional total porosity (PhiT con.).
In the wells Bu-52: all the correlations was strong.
In the wells Bu51 the strong correlations was between: -Logarithmic mean of COAT permeability (Log KCOAT) Logarithmic mean of SDR permeability (LogKSDR).

Conventional and NMR logs results Transformations
After making the correlation test between conventional logs results and NMR log results that represented in values of NMR permeability (KSDR and KCOAT), NMR total porosity (Ø T NMR), NMR effective porosity (Ø e NMR), conventional permeability (k con.), conventional total porosity (Ø T con.) and conventional effective porosity (Ø e con.), many transformations formulas appears with strong positive correlation as shown in Table (2) and appendix two:

Conclusion:
In the equation logk= a+bØ, the correlations of kcon with Ø e con. offered a better performance than with Ø T con. Than led to applied Ø e in the equation for more accurate results. When, the value of Ø T be approximately such as Ø e value, and this reflected the improvement in the flow properties and more homogenous porosity system because the