Computation of Productivity Index with Capillary Pressure Included and Its Application in Interpreting Production Data from Low-permeability Oil Reservoirs

2011 ◽  
Author(s):  
Kewen Li ◽  
Zengwei Chen
Keyword(s):  
Capillary Pressure ◽  
Oil Reservoirs ◽  
Productivity Index ◽  
Production Data ◽  
Low Permeability

Computation of Productivity Index With Capillary Pressure Included and Its Application in Interpreting Production Data From Low-Permeability Oil Reservoirs

SPE Journal ◽  
2012 ◽  
Vol 17 (04) ◽  
pp. 1041-1046 ◽  
Author(s):  
Kewen Li ◽  
Zengwei Chen
Keyword(s):  
Capillary Pressure ◽  
Oil Wells ◽  
Production Performance ◽  
Productivity Index ◽  
Production Data ◽  
Low Permeability ◽  
High Permeability ◽  
Core Samples ◽  
The Difference ◽  
Water Cut

Summary Capillary pressure might be ignored in high-permeability rocks, but it cannot be neglected in low-permeability rocks. To study the effect of capillary pressure on production performance in low-permeability oil wells or reservoirs, the formulas for calculating water cut and dimensionless total and oil productivity indices (PIs) were derived by considering capillary pressure. PI and water-cut data were computed using the new models with capillary pressure included. The results proved that PI increases with water cut in high-permeability rocks but decreases with the increase in water cut within a specific range in low-permeability rocks. Waterflooding experiments were then conducted in core samples with low and high permeabilities. The experimental waterflooding data demonstrated the same relationship between PI and water cut that was proved in the new PI model. Finally, the PI data were calculated using production data from oil wells, and the results were compared with the experimental data of the PI determined from coreflooding tests. The curves of PI vs. water cut, obtained from the production data of oil producers, were consistent with those inferred from waterflooding data in core samples. Note that the core plugs were sampled from the same oil wells. The new PI model was used to explain the difference in production performance between high- and low-permeability oil wells.

A New Unsteady-State Model for Calculating Oil-Water Relative Permeability of Low-Permeability/Ultra-Low Permeability Reservoirs

2012 ◽  
Vol 616-618 ◽  
pp. 964-969 ◽  
Author(s):  
Yue Yang ◽  
Xiang Fang Li ◽  
Ke Liu Wu ◽  
Meng Lu Lin ◽  
Jun Tai Shi
Keyword(s):  
Porous Media ◽  
Pressure Gradient ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
Oil Reservoirs ◽  
Flow In Porous Media ◽  
Low Permeability ◽  
Threshold Pressure ◽  
Flow Process ◽  
Threshold Pressure Gradient

Oil and water relative permeabilities are main coefficients in describing the fluid flow in porous media; however, oil and water relative permeability for low - ultra low perm oil reservoir can not be obtained from present correlations. Based on the characteristics of oil and water flow in porous media, the model for calculating the oil and water relative permeability of low and ultra-low perm oil reservoirs, which considering effects of threshold pressure gradient and capillary pressure, has been established. Through conducting the non-steady oil and water relative permeability experiments, oil and water relative permeability curves influenced by different factors have been calculated. Results show that: the threshold pressure gradient more prominently affects the oil and water relative permeability; capillary pressure cannot influence the water relative permeability but only the oil relative permeability. Considering effects of threshold pressure gradient and capillary pressure yields the best development result, and more accordant with the flow process of oil and water in low – ultra low perm oil reservoirs.

The Influence of Dynamic Capillary Pressure on the Seepage of Ultra-Low Permeability Reservoir

2014 ◽  
Vol 7 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Haiyong Zhang ◽  
Shunli He ◽  
Chunyan Jiao ◽  
Guohua Luan ◽  
Shaoyuan Mo
Keyword(s):  
Capillary Pressure ◽  
Low Permeability ◽  
Low Permeability Reservoir ◽  
Dynamic Capillary Pressure

The Mechanism of Flue Gas Injection for Enhanced Light Oil Recovery

2004 ◽  
Vol 126 (2) ◽  
pp. 119-124 ◽  
Author(s):  
O. S. Shokoya ◽  
S. A. (Raj) Mehta ◽  
R. G. Moore ◽  
B. B. Maini ◽  
M. Pooladi-Darvish ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Flue Gas ◽  
Gas Injection ◽  
Cost Effective ◽  
Air Injection ◽  
Oil Reservoirs ◽  
Flue Gases ◽  
Low Permeability ◽  
Light Oil ◽  
Light Oil Reservoirs

Flue gas injection into light oil reservoirs could be a cost-effective gas displacement method for enhanced oil recovery, especially in low porosity and low permeability reservoirs. The flue gas could be generated in situ as obtained from the spontaneous ignition of oil when air is injected into a high temperature reservoir, or injected directly into the reservoir from some surface source. When operating at high pressures commonly found in deep light oil reservoirs, the flue gas may become miscible or near–miscible with the reservoir oil, thereby displacing it more efficiently than an immiscible gas flood. Some successful high pressure air injection (HPAI) projects have been reported in low permeability and low porosity light oil reservoirs. Spontaneous oil ignition was reported in some of these projects, at least from laboratory experiments; however, the mechanism by which the generated flue gas displaces the oil has not been discussed in clear terms in the literature. An experimental investigation was carried out to study the mechanism by which flue gases displace light oil at a reservoir temperature of 116°C and typical reservoir pressures ranging from 27.63 MPa to 46.06 MPa. The results showed that the flue gases displaced the oil in a forward contacting process resembling a combined vaporizing and condensing multi-contact gas drive mechanism. The flue gases also became near-miscible with the oil at elevated pressures, an indication that high pressure flue gas (or air) injection is a cost-effective process for enhanced recovery of light oils, compared to rich gas or water injection, with the potential of sequestering carbon dioxide, a greenhouse gas.

Factors affecting water injection in the ultra-low permeability sandstone oil reservoirs

2021 ◽  
Author(s):  
Xuefen Liu ◽  
Fei Chen ◽  
Hongwu Xu ◽  
Yazhou Li ◽  
Siyang Wang ◽  
...  
Keyword(s):  
Water Injection ◽  
Oil Reservoirs ◽  
Low Permeability ◽  
Factors Affecting

Multi-Fracture Stimulation Techniques Make Better Wells in Ultra-Low Permeability Oil Reservoirs

2013 ◽  
Author(s):  
Yanrong CHANG ◽  
Hongjun LU ◽  
Baochun CHEN ◽  
Zhen-ning JI ◽  
Chengwang WANG ◽  
...  
Keyword(s):  
Oil Reservoirs ◽  
Low Permeability

Fractal Application in Micro Rock Mechanics of Low-Permeability Oil Reservoirs and Its Relationship with Enlarging Producing Reserves by Gemini Surfactant Flooding

2010 ◽  
Vol 29-32 ◽  
pp. 170-176 ◽  
Author(s):  
Heng Wei ◽  
Lei Wei ◽  
Jian Hui Yin ◽  
Fu Ling Yin ◽  
Jun Han Liu ◽  
...  
Keyword(s):  
Rock Mechanics ◽  
Gemini Surfactant ◽  
Fractal Dimensions ◽  
Oil Reservoirs ◽  
Low Permeability ◽  
Surfactant Flooding ◽  
High Permeability ◽  
Fractal Method ◽  
Pore Structures ◽  
Conventional Methods

Low permeability oil reservoirs were usually considered low quality reserves. However, low permeability oil reservoirs account for more and more percent of the proven reserves year by year in China. Conventional methods for analyzing medium-hign permeability cores are not suitable to low-permeability cores. Based on fractal method and the mercury injection curve data, the fractal dimensions of the pore structures of low permeability oil reservoirs are different from those of medium-high permeability oil reservoirs. The fractal dimensions of the pore structures of low permeability oil reservoirs are less than 2. Low permeability oil reservoirs which were not able to be developed are able to be developed by gemini surfactant flooding. This helps more and more low quality reserves be turned into producing reserves.

Utilizing Capillary Pressure Measurements and Water Saturation Logs to Determine Reservoir Quality in a Giant Middle Eastern Carbonate Field

2021 ◽  
Author(s):  
Bashar Alramahi ◽  
Qaed Jaafar ◽  
Hisham Al-Qassab
Keyword(s):  
Water Level ◽  
Capillary Pressure ◽  
Water Saturation ◽  
Middle Eastern ◽  
Free Water ◽  
Production Data ◽  
Reservoir Quality ◽  
Pressure Measurements ◽  
High Quality ◽  
Reservoir Facies

Abstract Classifying rock facies and estimating permeability is particularly challenging in Microporous dominated carbonate rocks. Reservoir rock types with a very small porosity range could have up to two orders of magnitude permeability difference resulting in high uncertainty in facies and permeability assignment in static and dynamic models. While seismic and conventional porosity logs can guide the mapping of large scale features to define resource density, estimating permeability requires the integration of advanced logs, core measurements, production data and a general understanding of the geologic depositional setting. Core based primary drainage capillary pressure measurements, including porous plate and mercury injection, offer a valuable insight into the relation between rock quality (i.e., permeability, pore throat size) and water saturation at various capillary pressure levels. Capillary pressure data was incorporated into a petrophysical workflow that compares current (Archie) water saturation at a particular height above free water level (i.e., capillary pressure) to the expected water saturation from core based capillary pressure measurements of various rock facies. This was then used to assign rock facies, and ultimately, estimate permeability along the entire wellbore, differentiating low quality microporous rocks from high quality grainstones with similar porosity values. The workflow first requires normalizing log based water saturations relative to structural position and proximity to the free water level to ensure that the only variable impacting current day water saturation is reservoir quality. This paper presents a case study where this workflow was used to detect the presence of grainstone facies in a giant Middle Eastern Carbonate Field. Log based algorithms were used to compare Archie water saturation with primary drainage core based saturation height functions of different rock facies to detect the presence of grainstones and estimate their permeability. Grainstones were then mapped spatially over the field and overlaid with field wide oil production and water injection data to confirm a positive correlation between predicted reservoir quality and productivity/injectivity of the reservoir facies. Core based permeability measurements were also used to confirm predicted permeability trends along wellbores where core was acquired. This workflow presents a novel approach in integrating core, log and dynamic production data to map high quality reservoir facies guiding future field development strategy, workover decisions, and selection of future well locations.

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