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Effect of heterogeneity on engineered water injection in carbonates using five-spot sector model:A numerical study

Petroleum 2022年第3期8卷 375-390页

作者： jamiu oyekan adegbite Emad Walid Al-Shalabi Petroleum Engineering Department Khalifa University of Science and TechnologySas Al Nakhl CampusAbu DhabiUnited Arab Emirates

One of the promising and emerging enhanced oil recovery techniques in both sandstones and carbonates is engineered water injection(EWI).However,few studies discussed the field-scale applications of this technique in heterogeneous carbonate *** paper is an extension of our previous work of the EWI technology at *** research numerically investigates heterogeneity effect on EWI technique in carbonates at field-scale using five-spot *** synthetic five-spot sector models were considered including homogeneous,heterogeneous with permeability channeling,and heterogeneous with gravity *** results showed that EWI improves both volumetric and displacement sweep efficiencies compared to conventional formation water injection(FWI)for all models ***,tracer method is recommended for better estimation of volumetric sweep efficiency as opposed to fractional flow ***,secondary EWI outperforms other techniques including secondary FW and tertiary *** addition,the observed delay in tertiary EWI can be reduced by increasing well injection pressure and sulfate concentration in the engineered *** optimum sulfate concentration of 25,000 ppm is recommended for achieving the highest oil recovery by *** study gives more insight into understanding the performance of the EWI technique at *** for boosting the performance of this technique have been discussed,which assure more certainty and lower risk.

关键词： Engineered water injection(EWI) Low salinity water injection(LSWI) Field application Permeability channeling Gravity underride

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Investigations on the relationship among the porosity,permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple regression analysis,artificial neural network and adaptive neuro-fuzzy interface system

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Petroleum Research 2021年第4期6卷 321-332页

作者： jamiu oyekan adegbite Hadi Belhaj Achinta Bera Petroleum Engineering Department Khalifa UniversityAbu DhabiUnited Arab Emirates Drilling Cementingand Stimulation Research CenterSchool of Petroleum TechnologyPandit Deendayal Energy UniversityGandhinagarGujarat382007India

Finding an accurate method for estimating permeability aside from well logs has been a difficult task for many *** most commonly used methods targeted towards regression technique to understand the correlation between pore throat radii,porosity and permeability are Winland and Pittman equation *** these methods are very common among petrophysicists,they do not give a good prediction in certain ***,this paper investigates the relationship among porosity,permeability,and pore throat radii using three methods such as multiple regression analysis,artificial neural network(ANN),and adaptive neuro-fuzzy inference system(ANFIS)for application in transition zone permeability ***,a comprehensive mercury injection capillary pressure(MICP)test was conducted using 228 transition zone carbonate core samples from a field located in the Middle-East *** regression analysis was later performed to estimate the permeability using pore throat and porosity *** the ANN,a two-layer feed-forward neural network with sigmoid hidden neurons and a linear output neuron was *** technique involves training,validation,and testing of input/output ***,for the ANFIS method,a hybrid optimization consisting of least-square and backpropagation gradient descent methods with a subtractive clustering technique was *** ANFIS combines both the artificial neural network and fuzzy logic inference system(FIS)for the training,validation,and testing of input/output *** results show that the best correlation for the multiple regression technique is achieved for pore throat radii with 35%mercury saturation(R35).However,for both the ANN and ANFIS techniques,pore throat radii with 55%mercury saturation(R55)gives the best *** the ANN and ANFIS are later found to be more effective and efficient and thus recommended as compared with the multiple regression technique commonly used in the industry.

关键词： Multiple regression analysis Artificial neural network Adaptive neuro-fuzzy interface system Permeability and porosity Pore throat Mercury injection capillary pressure

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