scholarly journals A new correlation for estimation of minimum miscibility pressure (MMP) during hydrocarbon gas injection

2020 ◽  
Vol 10 (6) ◽  
pp. 2349-2356
Author(s):  
Mohammad Fathinasab ◽  
Khalil Shahbazi
Author(s):  
Liqaa I. Hadi ◽  
Sameera M. Hamd-Allah

The important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was used to estimate MMP values for the two samples. The parameters of this equation have been tuned by splitting the plus component and regression process to obtain the best match for PVT properties between the calculated and that measured in the laboratory. Then the MMPs value compared with the results most reliable correlation.  Ternary diagram for these samples has been constructed to illustrate the occurrence of miscibility.


2017 ◽  
Vol 5 (2) ◽  
pp. 165-173
Author(s):  
IzuwaNkemakolam C. ◽  
◽  
NwabiaFrancis N. ◽  
OkoliNnanna O. ◽  
NwukoEjike S. ◽  
...  

SPE Journal ◽  
2021 ◽  
pp. 1-13
Author(s):  
Utkarsh Sinha ◽  
Birol Dindoruk ◽  
Mohamed Soliman

Summary Minimum miscibility pressure (MMP) is one of the key design parameters for gas injection projects. It is a physical parameter that is a measure of local displacement efficiency while subject to some constraints due to its definition. Also, the MMP value is used to tune compositional models along with proper fluid description constrained with other available basic phase behavior data, such as bubble point pressure and volumetric properties. In general, carbon dioxide (CO2) and hydrocarbon gases are the most common gases used for (or screened for) gas injection processes, and because of recent focus, they are used to screen for the coupling of CO2-sequestration and CO2-enhanced oil recovery (EOR) projects. Because the CO2/oil phase behavior is quite different than the hydrocarbon gas/oil phase behavior, researchers developed specialized correlations for CO2 or CO2-rich streams. Therefore, there is a need for a tool with expanded range capabilities for the estimation of MMP for CO2 gas streams. The only known and widely accepted measurement technique for MMP that is coherent with its formal definition is the use of a slimtube apparatus. However, the use of slimtube restricts the amount of data available, even though there are other alternative techniques presented over the last three decades, which all have various limitations (Dindoruk et al. 2021). Due to some of the complexities highlighted in Dindoruk et al. (2021) and time and resource requirements, there have been a number of correlations developed in the literature using mostly classical regression techniques with relatively sparse data using various combinations of limited input data (Cronquist 1978; Lee 1979; Yellig and Metcalfe 1980; Alston et al. 1985; Glaso 1985; Jaubert et al. 1998; Emera and Sarma 2005; Yuan et al. 2005; Ahmadi et al. 2010; Ahmadi and Johns 2011). In this paper, we present two separate approaches for the calculation of the MMP of an oil for CO2 injection: analytical correlation in which the correlation coefficients were tuned using linear support vector machines (SVMs) (Press et al. 2007; MathWorks 2020; RDocumentation 2020b; Cortes and Vapnik 1995) and using a hybrid method (i.e., superlearner model), which consists of the combination of random forest (RF) regression (Breiman 2001) and the proposed analytical correlation. Both models take the compositional analysis of oils up to heptane plus fraction, molecular weight of oil, and the reservoir temperature as input parameters. Based on statistical and data analysis techniques in combination with the help of corresponding crossplots, we showed that the performance of the final proposed method (hybrid method) is superior to all the leading correlations (Cronquist 1978; Lee 1979; Yellig and Metcalfe 1980; Alston et al. 1985; Glaso 1985; Emera and Sarma 2005; Yuan et al. 2005) and supervised machine-learning (Metcalfe 1982) methods considered in the literature (Altman 1992; Chambers and Hastie 1992; Chapelle and Vapnik 2000; Breiman 2001; Press et al. 2007; MathWorks 2020). The proposed model works for the widest spectrum of MMPs from 1,000 to 4,900 psia, which covers the entire range of oils within the scope of CO2 EOR based on the widely used screening criteria (Taber et al. 1997a, 1997b).


2021 ◽  
Author(s):  
Siqing Xu ◽  
Ahmed A BinAmro ◽  
Aaesha K. Al Keebali ◽  
Mohamed Baslaib ◽  
Shehadeh Masalmeh

Abstract Miscible CO2 flood is a well-established proven EOR recovery mechanism. There have been a large number of CO2 EOR developments worldwide, in both carbonate and clastic reservoirs. Potential control or influence factors on incremental production and incremental recovery over water flood are well documented in the published literature. Some of the published CO2 EOR developments have reported relatively high incremental recoveries. ADNOC is a leader in miscible gas injection EOR in carbonate reservoirs. There are a number of ongoing miscible gas injection EOR developments within its portfolio contributing a significant amount of production. Miscible CO2 flood is a key EOR development for ADNOC. Following intensive screening studies and laboratory experiments, the first CO2 EOR pilot in the MENA region was conducted as early as 2009 in one of ADNOC Onshore fields. This paved the way for further large-scale deployment and CO2 WAG pilots starting in 2016, both onshore. Appreciable progresses have been made since 2009. This bodes well with the significant initiatives undertaken by the UAE towards carbon emissions and greenhouse gas reduction, climate control and sustainable development. There are broad consensus that climate changes are now and will continue to affect all countries on all continents. Potential global warming can disrupt national economies and adversely impact on lives, costing people, communities and countries already today and perhaps more in the future. Carbon Capture, Utilization, and Storage (CCUS) technologies have been making headlines and attracting increasing amount of renewed attention, because they are in line with meeting global greenhouse gas reduction goals, and contributing towards climate control and sustainable development. The giant Abu Dhabi onshore field consists of 6 carbonate reservoirs. Several pilots, immiscible hydrocarbon gas injection and CO2 WAG, and a pattern immiscible gas injection WAG flood have been executed. Miscible gas injection EOR is therefore field proven. However, due to large field size, surface congestion constraints, geological and fluid variations, miscible gas injection EOR development by reservoir individually becomes complex and economically challenging. This paper presents a comprehensive study and recommends an integrated CCUS Hub development approach - enabling field-wide EOR development with several hundred million-barrels of incremental recovery. The study follows a step-by-step systematic method. Existing water flood performances were assessed first. History matched full field simulation then leads to identification of CO2 EOR targets by area/flank for each reservoir. These are referred to as sweet development areas. Available advanced PVT data were analysed and a multi-reservoir single equation of state developed. It has been found that only CO2 is miscible across all six reservoirs, while hydrocarbon gas is also miscible for the deepest two reservoirs. Dedicated fine scale sector models (EOR history matched where applicable) were developed to generate multiple CO2 EOR development scenarios, for example, depending on water flood maturity at the time of CO2 EOR start-up, and potential impact on incremental oil production, incremental oil recovery due to reservoir heterogeneity. First results from sector modelling show that quite a few areas/flanks would be sub-economical if CO2 EOR development on a stand-alone basis. Hence the concept of a CCUS Hub is proposed, which would allow sweet development areas in any or all of the six reservoirs to be developed from a single common surface Cluster. There is potential space for development phasing, allowing additional CO2 EOR developments within the same cluster area once ullage and CO2 supply becomes available. The CCUS Hub development approach facilitates optimization and sharing of injection/production flow-lines; surface space, gathering and processing facilities, CO2 supply, CO2 recovery unit deployment coupled with produced gas re-injection into the 2 deepest reservoirs. Compared to a more conventional development approach of reservoir by reservoir, considerable scope for CAPEX and OPEX savings was found. Assuming a constant future oil price, a reduction in development costs would allow more sweet development areas to pass the threshold of economical development, leading to an increase in overall incremental production and recovery from CO2 EOR.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Hao Zhang ◽  
Dali Hou ◽  
Kai Li

Minimum miscibility pressure (MMP), which plays an important role in miscible flooding, is a key parameter in determining whether crude oil and gas are completely miscible. On the basis of 210 groups of CO2-crude oil system minimum miscibility pressure data, an improved CO2-crude oil system minimum miscibility pressure correlation was built by modified conjugate gradient method and global optimizing method. The new correlation is a uniform empirical correlation to calculate the MMP for both thin oil and heavy oil and is expressed as a function of reservoir temperature, C7+molecular weight of crude oil, and mole fractions of volatile components (CH4and N2) and intermediate components (CO2, H2S, and C2~C6) of crude oil. Compared to the eleven most popular and relatively high-accuracy CO2-oil system MMP correlations in the previous literature by other nine groups of CO2-oil MMP experimental data, which have not been used to develop the new correlation, it is found that the new empirical correlation provides the best reproduction of the nine groups of CO2-oil MMP experimental data with a percentage average absolute relative error (%AARE) of 8% and a percentage maximum absolute relative error (%MARE) of 21%, respectively.


2019 ◽  
Author(s):  
Mohammad Rasheed Khan ◽  
Shams Kalam ◽  
Rizwan Ahmed Khan ◽  
Zeeshan Tariq ◽  
Abdulazeez Abdulraheem

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