CO2驱前缘运移规律及气窜时机预测方法——以胜利油田G89-1区块为例

doi:10.13809/j.cnki.cn32-1825/te.2022.05.005

Abstract

Abstract:

CO₂ gas channeling time prediction is of great significance for CO₂ gas channeling prevention and enhanced oil recovery. Current studies rarely involve quantitative characterization of the gas channeling time. According to the parameters of the target block reservoir, the crude oil viscosity, reservoir permeability, gas injection rate and injection-production well spacing and other factors impact on the moving rule of the CO₂ drive front is analyzed by the numerical simulation method, then the characterization formula of gas flow time and gas flow influence coefficient considering multiple factors is established, and the accuracy of the formula is verified by comparing with the field practice. The results show that under the condition of constant pressure production, the sweep efficiency decreases with the increase of crude oil viscosity. When the crude oil viscosity is greater than 3 mPa·s, the increase of gas emergence time slows down. When the reservoir permeability increases, the seepage resistance decreases, the displacement front moves faster, and the oil well breaks out earlier. When the gas injection velocity increases, the leading edge movement speed increases and the gas appearance time advances. When the gas injection velocity is 2 500 m³/d, the sweep efficiency is the minimum. When the injection-production well spacing increases, the moving speed of gas front slows down, and the gas emergence time of oil well prolongs. When the injection-production well spacing is larger than 250 m, the well spacing continues to increase, and the sweep efficiency increases slightly.

Key words: CO₂ flooding, quantitative characterization of gas channeling time, leading edge migration, reservoir numerical simulation, sweep efficiency

CLC Number:

CUI Chuanzhi,YAN Dawei,YAO Tongyu,WANG Jian,ZHANG Chuanbao,WU Zhongwei. Prediction method of migration law and gas channeling time of CO₂ flooding front: A case study of G89-1 Block in Shengli Oilfield[J].Petroleum Reservoir Evaluation and Development, 2022, 12(5): 741-747.

Figures/Tables 18

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编号	原油黏度（mPa·s）	渗透率（10^-3 μm²）	注入速度（m³/d）	井距（m）
1	1	4	1 500	98.98
2	1	6	2 500	247.45
3	1	8	3 500	148.47
4	1	10	2 000	296.94
5	1	12	3 000	197.96
6	2	4	3 500	247.45
7	2	6	2 000	148.47
8	2	8	3 000	296.94
9	2	10	1 500	197.96
10	2	12	2 500	98.98
11	3	4	3 000	148.47
12	3	6	1 500	296.94
13	3	8	2 500	197.96
14	3	10	3 500	98.98
15	3	12	2 000	247.45
16	4	4	2 500	296.94
17	4	6	3 500	197.96
18	4	8	2 000	98.98
19	4	10	3 000	247.45
20	4	12	1 500	148.47
21	5	4	2 000	197.96
22	5	6	3 500	98.98
23	5	8	1 500	247.45
24	5	10	2 500	148.47
25	5	12	3 500	296.94

因素	回归方程	R²	平均误差（%）
见气时间（d）	T=0.003 5 μ^0.373K^-1.018V^-0.213L^2.435+354.81	0.974	2.25
波及系数（见气时）（%）	S=0.045 μ^0.011K^-1.361V^0.053L^1.321+24.22	0.940	1.29

Prediction method of migration law and gas channeling time of CO₂ flooding front: A case study of G89-1 Block in Shengli Oilfield

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Prediction method of migration law and gas channeling time of CO2 flooding front: A case study of G89-1 Block in Shengli Oilfield

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Prediction method of migration law and gas channeling time of CO₂ flooding front: A case study of G89-1 Block in Shengli Oilfield