Reservoir water saturation and permeability modeling in the Pangkah field

2018 ◽  
Author(s):  
S. Sutiyono
Keyword(s):  
Water Saturation ◽  
Reservoir Water ◽  
Permeability Modeling

scholarly journals Characterization of Mishrif Formation Reservoir in Amara Oil Field, Southeast Iraq, Using Geophysical Well-logging

2021 ◽  
pp. 4702-4711
Author(s):  
Asmaa Talal Fadel ◽  
Madhat E. Nasser
Keyword(s):  
Reservoir Characterization ◽  
Gamma Ray ◽  
Water Saturation ◽  
Total Porosity ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Reservoir Water ◽  
Resistivity Logs ◽  
Reliable Knowledge

     Reservoir characterization requires reliable knowledge of certain fundamental properties of the reservoir. These properties can be defined or at least inferred by log measurements, including porosity, resistivity, volume of shale, lithology, water saturation, and permeability of oil or gas. The current research is an estimate of the reservoir characteristics of Mishrif Formation in Amara Oil Field, particularly well AM-1, in south eastern Iraq. Mishrif Formation (Cenomanin-Early Touronin) is considered as the prime reservoir in Amara Oil Field. The Formation is divided into three reservoir units (MA, MB, MC). The unit MB is divided into two secondary units (MB1, MB2) while the unit MC is also divided into two secondary units (MC1, MC2). Using Geoframe software, the available well log images (sonic, density, neutron, gamma ray, spontaneous potential, and resistivity logs) were digitized and updated. Petrophysical properties, such as porosity, saturation of water, saturation of hydrocarbon, etc. were calculated and explained. The total porosity was measured using the density and neutron log, and then corrected to measure the effective porosity by the volume content of clay. Neutron -density cross-plot showed that Mishrif Formation lithology consists predominantly of limestone. The reservoir water resistivity (Rw) values of the Formation were calculated using Pickett-Plot method.   

scholarly journals Flooding mechanism of biolithite based on progressive ion exchange model: an example of the Wangxuzhuang biolithite reservoir in the Dagang oilfield

2021 ◽  
Vol 18 (3) ◽  
pp. 369-378
Author(s):  
Jianmeng Sun ◽  
Xindi Lv ◽  
Jie Zong ◽  
Shuiping Ma ◽  
Yong Wu ◽  
...  
Keyword(s):  
Ion Exchange ◽  
Water Saturation ◽  
Water Injection ◽  
Ct Scanning ◽  
Exchange Model ◽  
Water Flooding ◽  
Formation Water ◽  
Reservoir Water ◽  
Factors Affecting ◽  
Formation Resistivity

Abstract The biolithite reservoir has a strong heterogeneity and complex pore structure, and the changing trend of formation resistivity is complicated during the waterflood development process. In the logging interpretation of a water-flooded layer, mixed-formation water resistivity is a critical parameter and its accurate calculation heavily influences the evaluation of logging water saturation. The commonly used mixed liquid resistivity models have not taken into account the contribution of irreducible clay water and, thus, they are not suitable for biolithite reservoirs with high shale contents. In this paper, a new 3D digital core was constructed based on CT scanning, and a progressive ion exchange model of the mixed-formation water compatible with the biolithite reservoir put forward. Compared with experimental data from core water flooding, the progressive ion exchange model conforms to the resistivity change law of biolithite reservoirs. Through numerical simulation and analysis of the resistivity of biolithite reservoir, it is concluded that the salinity of injected water and the formation water saturation are the main factors affecting the resistivity characteristics of water-flooded layer. In terms of the interpretation of the water-flooded layer, the water saturation was calculated using the progressive ion exchange model through finite element modelling of formation resistivity. The particular mechanism of water flooding and changing law of rock electrical properties during reservoir water injection development are presented, which provide a new reliable basis for optimization of the biolithite reservoir development plan.

scholarly journals Determination of Petrophysical Parameters of Reservoir Rock with a Special Look to Shale Effect (Case Study: One of the Gas Fields in Southern Iran)

2021 ◽  
Vol 5 (2) ◽  
pp. 1-10
Author(s):  
Taheri K
Keyword(s):  
Water Saturation ◽  
Accurate Determination ◽  
Reservoir Rock ◽  
Petrophysical Properties ◽  
Gas Reservoir ◽  
Reservoir Water ◽  
Petrophysical Parameters ◽  
Hydrocarbon Reservoir ◽  
Shale Volume

Determination of petrophysical parameters is necessary for modeling hydrocarbon reservoir rock. The petrophysical properties of rocks influenced mainly by the presence of clay in sedimentary environments. Accurate determination of reservoir quality and other petrophysical parameters such as porosity, type, and distribution of reservoir fluid, and lithology are based on evaluation and determination of shale volume. If the effect of shale volume in the formation not calculated and considered, it will have an apparent impact on the results of calculating the porosity and saturation of the reservoir water. This study performed due to the importance of shale in petrophysical calculations of this gas reservoir. The shale volume and its effect on determining the petrophysical properties and ignoring it studied in gas well P19. This evaluation was performed in Formations A and B at depths of 3363.77 to 3738.98 m with a thickness of 375 m using a probabilistic calculation method. The results of evaluations of this well without considering shale showed that the total porosity was 0.1 percent, the complete water saturation was 31 percent, and the active water saturation was 29 percent, which led to a 1 percent increase in effective porosity. The difference between water saturation values in Archie and Indonesia methods and 3.3 percent shale volume in the zones show that despite the low shale volume in Formations A and B, its effect on petrophysical parameters has been significant. The results showed that if the shale effect not seen in the evaluation of this gas reservoir, it can lead to significant errors in calculations and correct determination of petrophysical parameters.

Principal component analysis (PCA) based hybrid models for the accurate estimation of reservoir water saturation

2020 ◽  
Vol 145 ◽  
pp. 104555 ◽  
Author(s):  
Solomon Asante-Okyere ◽  
Chuanbo Shen ◽  
Yao Yevenyo Ziggah ◽  
Mercy Moses Rulegeya ◽  
Xiangfeng Zhu
Keyword(s):  
Principal Component Analysis ◽  
Water Saturation ◽  
Principal Component ◽  
Component Analysis ◽  
Hybrid Models ◽  
Accurate Estimation ◽  
Reservoir Water

Material Balance Calculations with Water Influx in the Presence of Uncertainty in Pressures

1962 ◽  
Vol 2 (02) ◽  
pp. 120-128 ◽  
Author(s):  
C.R. Mcewen
Keyword(s):  
Least Squares ◽  
Water Saturation ◽  
Material Balance ◽  
Production Data ◽  
Petroleum Reservoir ◽  
Gas Reservoirs ◽  
Reservoir Water ◽  
Water Influx ◽  
Material Balance Calculation ◽  
Line Fitting

Abstract This paper presents a technique for calculating the original amount of hydrocarbon in place in a petroleum reservoir, and for determining the constants characterizing the aquifer performance, based on pressure-production data. A method for doing this based on a least-squares line-fitting computation was proposed by van Everdingen, Timmerman and McMahon in 1953. We found that their method would not work when there is error in the reservoir pressure dataeven moderate error. The technique presented here appears to give reasonable answers when pressure data are uncertain to the degree expected in reservoir pressure determinations. The major change introduced in the present analysis is to limit the least-squares line-fitting to yield only one constant the amount of hydrocarbon in place. The water-influx constant is then taken as proportional to the oil (or gas) in place. The constant of proportionality can be computed from estimates of effective compressibility and reservoir water saturation. It is also pointed out that the commonly used least-squares analysis assumes all of the uncertainty to be in the dependent variable. The material balance should be arranged so that this condition is fulfilled if correct inferences are to be made from statistical calculations. Examples are shown of the application of the new technique to gas reservoirs both hypothetical and real and to the oil reservoir example of van Everdingen, Timmerman and McMahon. Introduction The amount of hydrocarbon originally in place in a petroleum reservoir can be estimated by means of the material-balance calculation. Simultaneous observations of pressure and amounts of produced fluids are required, together with the PVT data applicable to the reservoir fluids. If water encroachment is occurring, it is desirable to try to infer the behavior of the aquifer, as well as the original hydrocarbon in place, from the pressure-production data. This imposes additional demands on the method of calculation, and uncertainty in the data can result in large uncertainty in the answer. In addition, if the size of a gas cap is to be established, the whole problem becomes indeterminate, as pointed out by Woods and Muskat. Brownscombe and Collins simulated a gas reservoir and its aquifer on a reservoir analyzer and derived quantitative information on the effect of uncertainty in pressure and aquifer permeability on computed gas in place. Among the various techniques of estimating the performance of an aquifer, the method of van Everdingen and Hurst, based on compressible flow theory, seems to have been the most generally successful (see Ref. 4, for example). In this paper we shall confine ourselves to their representation of the aquifer. In 1953, van Everdingen, Timmerman and McMahon introduced a statistical technique for deriving the amount of oil originally in place and the parameters which describe the aquifer. (We shall refer to this technique as the "VTM method", as suggested by Mueller.) Their example reservoir had no gas cap. It has been our experience that the VTM method gives a reasonable answer when the data are very accurate, but that inaccuracy (particularly in pressure) can cause the method to break down. The effect was first observed in gas reservoirs, but has since been seen in oil reservoirs also. In this paper we present another statistical method which has been successful in achieving a reasonable answer where the VTM method has failed. In the new method, one less parameter is derived from material-balance computations. It is assumed that values can be established for effective compressibility in the aquifer and reservoir water saturation independently of the material-balance calculation. The water-influx constant can then be obtained from these data and the quantity hydrocarbon in place. SPEJ P. 120^

ELECTRICAL PARAMETERS OF THE UPPER CARBON ROCKS (RUNOVSHCHYNSKA AREA OF THE DNIEPER-DONETSK BASIN)

2019 ◽  
pp. 37-45
Author(s):  
S. Vyzhva ◽  
V. Onyshchuk ◽  
I. Onyshchuk ◽  
M. Reva ◽  
O. Shabatura
Keyword(s):  
Electrical Resistivity ◽  
Water Saturation ◽  
Pore Space ◽  
Donets Basin ◽  
Electrical Parameters ◽  
Reservoir Water ◽  
Reservoir Conditions ◽  
Porosity Coefficient ◽  
Specific Electrical Resistivity ◽  
Formation Resistivity

The main objective of this article is to study electrical parameters of sandstones and argillites of the Upper Carbon rocks in the Runovshchynska area of the Dnieper-Donets basin. It has been determined that specific electrical resistivity of dry rock samples (specific electrical resistivity of rock matrix) varies from 44,802 kΩ·m to 6,115 МΩ·m (average 751,328 kΩ·m). Specific electrical resistivity of sandstones is 3,45 times more than argillitesdue to different shaliness of studied rocks. Specific electrical resistivity of saturated rocks samples varies from 0,54 Ω·m to 10,46 Ω·m (average 1,23 Ω·m). Specific electrical resistivity of argillites is 2,46 times more than sandstones because the latter had high content of reservoir water in their pores (sandstones had better conductivity). It has been determined that formation resistivity factor of sandstones in atmospheric conditions varies from 6,05 to 33,71 (argillites 11,8), and argillites – from 4,76 to 51,47 (average 17,4). Physical modelling of reservoir conditions (temperature t = 78,5°С, pressure p = 31–31,9 MPa, mineralization M= 170 g/l) showed that specific electrical resistivity varies from 0,3 Ω·m to 3,0 Ω·m (average 0,75 Ω·m). Sandstones in reservoir conditions had the range from 0,3 Ω·m to 2,3 Ω·m (average 0,7 Ω·m), and argillites – from 0,5 Ω·m to 3,0 Ω·m (average 1,2 Ω·m). In this case, specific electrical resistivity of argillites is 1,6 times more than sandstones. Due to the closure of microcracks and the deformation of the pore space, the electrical resistance of rocks increases with increasing pressure. The dependence of formation resistivity enlargement factor on pressure for the studied rocks is expressed by 2-order polynomials. The formation resistivity factor of the studied rocks in reservoir conditions has been determined. It was defined that sandstones in reservoir conditions had the range of the formation resistivity factor from 5,4 to 63,3 (average 20,3), and porosity coefficient – from 0,038 to 0,175 (average 0,113). The range of the formation resistivity factor for argillites was from 13,4 to 88,7 (average 34,3), and porosity coefficient – from 0,043 to 0,115 (average 0,086). Analysis of data of laboratory electrometric investigations has allowed establishing correlations between the porosity coefficient and formation resistivity factor. In addition, the correlation of electrical parameters of rocks in atmospheric and reservoir conditions and the formation resistivity enlargement factor from the water saturation coefficient, taking into account the lithological varieties of the studied rocks, was established.

Experimental Study on Reducing Water Phase Trapping in Tight Gas Reservoirs

2013 ◽  
Vol 295-298 ◽  
pp. 3293-3297
Author(s):  
Hao Zhang ◽  
Xiao Ning Feng ◽  
Ji Ping She ◽  
Fu You Huang ◽  
Guan Fang Li
Keyword(s):  
Water Saturation ◽  
Water Phase ◽  
Tight Gas ◽  
Prevention Measures ◽  
Gas Reservoirs ◽  
Reservoir Water ◽  
Tight Gas Reservoirs ◽  
Western Sichuan ◽  
Water Based ◽  
Western Sichuan Basin

This document explains and demonstrates how to reduce water phase trapping in tight gas reservoirs during drilling. The water phase trapping laboratory device and experiment method has been studied, through the experiments on reservoir water phase trapping of western Sichuan Basin in China, Knowing that the damage is very serious, water self absorption experiments with different periods show that porosity and permeability of cores are basically above 50%. for the reason, the high capillary pressure and low water saturation are the main factors. Water phase trapping damage prevention measures has been put forward, including avoiding using water-based operating fluid as much as possible, minimizing or even avoiding the invasion of water-based operating fluid, and reducing interfacial tension and promote smooth operating fluid flow back.

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