CO2驱最小混相压力预测模型研究

doi:10.13809/j.cnki.cn32-1825/te.2022.05.006

Abstract

Abstract:

Based on the analysis of the factors influencing the minimum miscibility pressure in CO₂ flooding and 36 groups of tubule experimental data, the correlation degree of each factor influencing the minimum miscibility pressure in CO₂flooding of crude oil is calculated by the grey correlation method. The prediction model of minimum miscible pressure in CO₂ flooding for crude oil is fitted by the MATLAB （Matrix Laboratory） software, which is related to the reservoir temperature, relative molecular weight of C₅₊, volatile hydrocarbon component （N₂+CH₄） content and intermediate hydrocarbon component （CO₂+H₂S+C₂—C₄） content. The fitting correlation coefficient reaches 0.900 9. The data of the minimum miscible pressure test of three wells in an oilfield are used to verify the new prediction model. The average error of calculation is 3.57 %, which can be used to guide the field development of the reservoirs.

Key words: CO₂flooding, minimum miscible pressure, grey correlation method, prediction model, tubule experiment

CLC Number:

TE341

Yi PAN,Qiuxia ZHAO,Lei SUN, et al. Prediction model of minimum miscible pressure in CO₂ flooding[J]. Petroleum Reservoir Evaluation and Development, 2022, 12(5): 748-753.

Figures/Tables 5

Fig. 1

Table 1

Data of influencing factors of minimum miscible pressure[17⇓⇓⇓⇓-22]"

序号	t（℃）	M_C5+	M_C7+	X_vol（%）	X_int（%）	X_C2—C4（%）	X_C2—C6（%）	MMP（MPa）
1	96.60	217.00	224.00	0.04	7.39	6.99	10.96	26.62
2	103.00	222.30	233.10	0.08	4.45	3.95	9.89	29.23
3	110.00	262.40	269.70	0.10	1.05	1.05	4.37	29.34
4	84.00	202.90	208.40	0.18	2.18	0.85	5.85	22.11
5	107.00	284.50	320.60	0.18	10.02	8.67	13.30	29.54
6	101.60	301.00	310.00	1.77	4.35	3.72	7.19	31.30
7	99.00	254.00	265.00	1.97	11.78	11.44	15.39	22.30
8	108.00	283.00	293.00	2.13	6.80	6.32	9.52	27.90
9	101.00	265.00	275.00	0.48	13.64	6.47	9.95	24.10
10	66.00	380.00	391.00	1.63	11.84	11.46	13.37	20.00
11	106.00	224.00	233.00	2.34	6.20	7.04	10.69	26.00
12	42.80	204.00	222.00	17.00	26.31	25.31	28.80	10.69
13	32.20	188.00	206.00	11.00	16.24	15.26	25.00	7.58
14	110.00	181.00	185.00	33.00	32.15	30.12	36.00	20.20
15	71.10	221.00	227.00	41.00	6.84	6.25	7.00	23.44
16	102.20	205.00	210.00	51.00	7.56	6.99	10.00	28.17
17	67.80	204.00	210.00	31.00	22.15	21.30	23.00	16.89
18	112.20	214.00	220.00	33.00	18.26	16.23	28.00	24.15
19	80.00	241.00	245.00	53.00	8.12	2.36	9.00	26.75
20	31.10	205.00	240.00	12.00	19.45	15.23	24.20	8.10
21	73.30	210.00	218.00	49.00	6.89	6.25	8.84	24.13
22	40.00	202.00	221.00	24.00	25.46	23.54	30.70	9.07
23	54.40	169.00	190.00	30.00	30.14	28.46	37.30	11.78
24	48.90	214.00	227.00	16.00	25.16	24.13	31.00	10.58
25	40.00	191.00	205.00	9.30	21.05	14.26	31.00	8.78
26	78.90	265.02	279.88	31.68	22.15	4.62	5.81	23.11
27	112.00	274.16	280.25	17.28	15.26	8.26	10.62	25.21
28	43.60	230.76	265.48	8.73	9.23	5.43	7.31	13.56
29	97.00	213.20	225.40	9.97	14.23	5.12	6.88	19.96
30	68.00	203.12	214.83	14.89	6.25	3.15	7.73	17.29
31	103.30	195.04	202.69	45.29	28.47	16.24	20.15	22.70
32	80.00	168.23	197.00	13.00	45.50	13.24	14.12	23.45
33	121.10	241.00	245.38	26.58	30.25	7.45	8.56	23.60
34	72.90	214.00	220.98	55.18	10.39	3.21	4.26	40.50
35	120.80	302.15	319.00	30.67	18.89	6.58	10.24	41.15
36	92.60	187.64	198.00	57.13	24.23	7.16	9.95	34.20

Table 1

Table 2

Fig. 2

Table 3

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井号	t （℃）	M_C5+	X_vol （%）	X_int （%）	实验值（MPa）	计算值（预测值）（MPa）	相对误差的绝对值（%）	相对误差绝对值的平均值（%）
1	123.62	226.59	32.05	11.22	45.85	43.18	3.52	3.57
2	115.95	255.28	52.55	8.02	47.06	45.94	0.73
3	120.76	454.01	21.46	8.71	54.08	56.59	6.46

Prediction model of minimum miscible pressure in CO₂ flooding

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Prediction model of minimum miscible pressure in CO2 flooding

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Prediction model of minimum miscible pressure in CO₂ flooding