Journal of Petroleum Science and Technology
Volume:11 Issue: 3, Summer 2021

A detailed description of the carbonate reservoir is an important step in preparing a field development plan. An accurate determination of petrophysical parameters and rock characteristics are key parameters in the carbonate reservoir description. The rock properties are traditionally obtained from different techniques such as lab measurement, well logging, well test, etc. In this manuscript, data from core measurements and NMR measurements are analyzed to study the petrophysical properties of Cretaceous carbonate rock from Asmari Formation. First, the pore size, pore system, porosity and permeability are determined from the core measurements and NMR Analysis. Second, the results of core and NMR evaluations are compared, and the reasons for differences are distinguished. Comparison between the porosity values demonstrates that porosity from NMR and helium injection experiments are very similar in which the average porosity is 21.4 % and NMR porosity is 20.68%. Afterwards, pore sizes received from the NMR model show reliable results and match the pore size distribution determined from the MICP experiment. The permeability value is modeled with NMR permeability predicting models, namely Standard Kenyon and Timur-Coates. Adjusted NMR Permeability results are 17.7 (mD) and 18 (mD) for (SDR) and (TC) methods, respectively, and they are consistent with laboratory core permeability results (Kg=22, Kl=19.2, Kw=18.4). The pore throat distributions are also similar for two NMR and core measurement methods. This study shows how NMR analysis could be useful in determining petrophysical parameters. Ultimately, the results for reservoir characteristics of carbonate rock obtained by core and NMR experiments are compared quantitatively and qualitatively.

The reservoir heterogeneity controls interwell connectivity and affects reservoir dynamics. An approach is to use continuum percolation to study the flow behavior of low to intermediate net-to-gross reservoirs. In this study, reservoir models with a permeability contrast have been used, and the interwell connectivity between two wells and the remaining unswept oil has been determined. The percolation parameters, including the amount of recoverable oil connected between two wells and the amount of unswept oil (also referred to as dangling end fraction (that control fluid displacement (e.g. waterflooding) vary as a function of sand body size and reservoir size. These properties show a power-law function of net-to-gross (i.e. occupation fraction) with some exponents called critical exponents. There exist a few publications on the numerical values of these parameters. The main contribution of this study is to investigate the effects of reservoir anisotropy on the percolation parameters. To determine the swept (backbone) fraction connected between two wells, the flow-based criteria depending on the system size have been proposed. The results show that the critical exponents for the backbone and dangling ends are in the range of 0.3to 0.45 and -0.45 to -0.20.   It is notified that the limitation to perform simulations on infinite systems results in a range for these exponents, although there exist unique values for infinite systems. Moreover, a sensitivity analysis is implemented to find the correct flow-based criteria for the backbone. The results of this study extend the applicability of the percolation properties curves for anisotropic reservoirs.

The study of microscopic remaining oil is of great significance for the effective development of reservoirs after water flooding. An observation and quantitative characterization method of occurrence states of remaining oil on pore scale is proposed in this manuscript. Core columns are frozen immediately after the displacement experiment with liquid nitrogen freezing technology, and the samples are ground to a thickness of 0.05 mm under frozen conditions. Distributions of oil and water in pores are observed with the technology of ultraviolet fluorescence microphotography. The remaining oil content of different types is quantitatively calculated by analysis of characteristic parameters of the core image. Quantitative analysis of the laboratory displacement experimental results indicated that the average oil recovery reaches over 48% after water flooding. The main types of the remaining are throat state, cant state, thin film on pore surface, cluster state, interparticle adherence state and particle adherence state. Their relative contents account for 1.84%, 3.07%, 37.42%, 5.83%, 27.91% and 24.23% of total remaining oil reserves, respectively. Among them, the remaining oil in a thin film on pore surface, remaining oil of interparticle adherence, and remaining oil of particle adherence with high content are the development targets after water flooding. Based on determining the type and distribution characteristics of the microscopic remaining oil, the mechanism and influential factors of different types of microscopic remaining oil are analyzed, and the exploitation method for different types of remaining oil is proposed. This study is of great significance for guiding the development of remaining oil after water flooding and improving enhanced oil recovery.

Nowdays, sand production is one of the most important challenges in the oil and gas industries, making numerous issues. To prevent these problems, it is necessary to use mathematical models to estimate the sand production onset and the amount of sand produced during production. There are generally four methods for predicting sand production: experimental methods that use field observations and well data, laboratory simulations, numerical methods, and analytical methods. In this research, a novel numerical method is proposed to estimate the amount of sand production. First, it is necessary to estimate the onset of sand production using failure criteria and after that, the amount of sand production is estimated. First, to use numerical methods, they must be calibrated by using field data. In this paper, the proposed numerical model is calibrated by using the field observations and well data of a North Sea reservoir. It is used to predict the amount of produced sand that the average relative error of the proposed method was about 6.9%. Also, in this model, computable parameters are used to calculate the amount of sand production, which reduces the error of this method. It also shows that this is a practical model. Therefore, the proposed model is reliable, and it can be used to estimate the amount of sand production for subsequent years. The proposed model is developed based on incompressible and slightly compressible fluids; this paper also considers the relationship between porosity and permeability at steady-state conditions. Ultimately, sensitivity analysis on sand production is performed, and the effects of four permeability parameters: uniaxial compressive strength, maximum horizontal stress, and wellbore pressure on sand production are checked.

Generating pressure transient response for an interpretation model to describe essential features of a reservoir system accurately is often difficult. It is generally due to the inaccessibility of standard pressure transient analysis tools due to the cost, and even when accessible, they are constrained to its workflow and limitations. This study presents an alternative to standard industry tools to determine transient pressure response for a given rate history. A reservoir model for a single well with constant skin and wellbore storage producing a varying step rate in a semi-infinite acting reservoir with a sealing fault was used as a case study. The well is also assumed to be producing above saturation pressure from a reservoir saturated with slightly compressible fluid hence having constant fluid properties. The method discussed in this study can be applied to well-test interpretation models with an analytical constant terminal rate solution producing at variable step rates from a reservoir having constant rock and fluid properties. The results show conformance with that of standard industry software, and diagnostic plots of the simulated data set can help engineers plan well-test jobs and study the behavior of different reservoir models. Moreover, the program can be modified and used to regress observed pressure response with a selected model. The approach suggested by this study is a perfect alternative where time and cost are constraints.

Rock typing has been utilized in numerous studies where it has been proven to be a powerful tool  for determining rock properties and estimating unknown parameters such as permeability. It can be performed based on routine core analysis (RCAL) or special core analysis (SCAL) data, and the accuracy of results could be different. Because of the high cost and time-consuming process of special core analysis, SCAL data are not available in all wells of a reservoir. Hence, in this study, a practical workflow is carried out using RCAL data. For this purpose, the data of four wells in a reservoir have been used. After utilizing three HFU (Hydraulic Flow Units), Winland r35 and lithology methods, the results showed that the best and the most accurate rock typing method is Winland r35 method. In the next step, several approaches were used to estimate permeability, and it was observed that the combination of the multi-resolution graph-based clustering (MRGC) method in GEOLOG software and Winland r35 method in this carbonate reservoir is the best estimation approach. The correlation coefficient (R2), between measured and estimated permeability was approximately 0.96. Eventually, when the only available data are the RCAL data, the presented algorithm yields a high degree of accuracy.