松辽盆地重点油区水热型砂岩地热储层评价

刘先录; 胡光明; 肖红平; 周玉钦; 张庭瑀; 饶松

doi:10.19509/j.cnki.dzkq.tb20240530

松辽盆地重点油区水热型砂岩地热储层评价

doi: 10.19509/j.cnki.dzkq.tb20240530

刘先录^1a,,
胡光明^{1a, 1b, 1c, ,},
肖红平²,
周玉钦^1a,
张庭瑀^1a,
饶松^{1a, 1b, 1c}

1a .
长江大学：地球科学学院
1b .
长江大学：非常规油气地质与工程湖北省工程研究中心
1c .
长江大学：南方复杂页岩油气地质与开发湖北省重点实验室，武汉 430100
2 .
中国石油勘探开发研究院，北京 100083

基金项目: 国家自然科学基金项目（41472097）；中国石油天然气股份有限公司油气与新能源板块2022—2023年度科技课题（2022KT2601）

详细信息

作者简介:
刘先录：E-mail：19525516589@163.com

通讯作者:
E-mail：hugm@yangtzeu.edu.cn

中图分类号: P314
计量
- 文章访问数: 353
- PDF下载量: 22
- 被引次数: 0
出版历程
- 收稿日期: 2024-09-18
- 录用日期: 2025-03-05
- 修回日期: 2025-03-05
- 网络出版日期: 2025-03-05

Hydrothermal sandstone geothermal-reservoir evaluation of the key oil-producing area in the Songliao Basin

LIU Xianlu^{1a
,},
HU Guangming^{1a, 1b, 1c
, ,},
XIAO Hongping²,
ZHOU Yuqin^1a,
ZHANG Tingyu^1a,
RAO Song^{1a, 1b, 1c}

1a .
School of Geosciences, Yangtze University
1b .
Hubei Engineering Research Center of Unconventional Petroleum Geology and Engineering, Yangtze University
1c .
Hubei Key Laboratory of Complex Shale Oil and Gas Geology and Development in Southern China, Wuhan 430100, China, Yangtze University
2 .
PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China

More Information

Author Bio:
E-mail：19525516589@163.com

Corresponding author: E-mail：hugm@yangtzeu.edu.cn

摘要

摘要:
现行的热储行业评价标准是基于有水优储（中高孔中高渗）制定的，按此标准我国大多数盆地的热储属于有水差储（中低孔低渗），故现行热储行业评价标准存在不适应性。另外，在地热资源预可行性勘查阶段，常用的评价方法需要大量的参数和数据，而这一阶段能获取的资料往往较少，因此，探索少参数的快速评价方法很有必要。松辽盆地重点油区的水热型砂岩热储具有中薄层中低孔低渗的特点，属于有水差储，本研究以此为例，探索研究有水差储的评价标准及少参数条件下热储的快速评价方法。首先，在了解了目的层热储的厚度、孔隙度和渗透率等基本特征的基础上，对其进行统计分析，应用黄金分割法划分等级，确定这些参数的评价标准。由于其属于低温热储，单井日产水量对热储的评价更为重要，选取开发区的砂体厚度、孔隙度、渗透率和单井日产水量数据，利用多元线性回归对其进行分析后构建热储评价公式，计算各评价单元的得分，并按照黄金分割法划分等级。将此方法的得分排名与现有2种评价方法的两两对比表明，纳入砂体厚度而弃用温度是合理的，且此方法的得分标准差较大，能够更好地反映各评价单元之间的差异，因此，此方法较为可行，针对有水差储制定的评价标准较为合理。本研究所确定的有水差储评价标准对其他盆地的热储评价有一定的参考意义，考虑到各盆地之间的差异，本研究确定的少参数快速评价方法对其他盆地不一定适用，但是确定评价公式的过程有借鉴意义。
- 松辽盆地 /
- 水热型砂岩 /
- 有水差储 /
- 地热储层评价标准 /
- 地热储层评价方法
Abstract: <p>Current industry criteria for geothermal-reservoir classification were established for high-quality hydrothermal systems (medium–high porosity and permeability). Consequently, most Chinese basinal reservoirs exhibit medium to low porosity and low permeability are misclassified as "poor," rendering the standards inapplicable. Moreover, the multi-parameter methods commonly used in pre-feasibility assessments require extensive data sets that are seldom, available during early exploration phases. Rapid, low-parameter evaluation protocols are therefore urgently needed. </p></sec><sec><title>Objective
Hydrothermal sandstone reservoirs in the Songliao Basin's key oil-producing area are typified by medium–thin beds, medium–low porosity, and low permeability. These characteri-stics are traditionally labelled as "poor." Using these reservoirs as a case study, we recalibrate the classification criteria for low-quality hydrothermal systems and develop parsimonious, rapid-assessment protocols that minimize data requirements.
Methods
First, the fundamental reservoir characteristics (thickness, porosity, and permeability) were statistically analyzed. The Golden Section Method was applied to classify parameter levels and establish evaluation criteria. Second, given the limited temperature variation among the studied low-temperature geothermal reservoirs, single-well daily production rate emerged as a critical evaluation metric. Consequently, sand body thickness, porosity, permeability, and single-well daily production rate within the study area were selected as input variables. Multivariate linear regression analysis was employed to derive a geothermal reservoir evaluation formula. This formula was then used to calculate evaluation unit scores, with final grading established using the Golden Section Method.
Results
Pairwise comparison of the score rankings from this method against those of two established evaluation methods demonstrated the validity of incorporating sand body thickness while excluding temperature. Furthermore, the relatively high standard deviation of the scores obtained by this method enhances its ability to delineate variations among the evaluation units. Consequently, this approach demonstrates greater feasibility, and the formulated evaluation criteria are particularly well-suited for hydrothermal reservoirs with limited storage capacity.
Conclusion
The evaluation criteria for low-storage hydrothermal systems developed in this study provide a valuable reference for geothermal-reservoir assessment in other basins. While basin-specific heterogeneity limits the direct transferability of the concise, few-parameter rapid-assessment model, the methodological framework used to derive the evaluation equation offers a robust, replicable template for analogous studies.
- Songliao Basin /
- hydrothermal sandstone /
- poor-storage aquifer /
- geothermal-reservoir evaluation criterion /
- geothermal-reservoir assessment methodology

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图 1 松辽盆地地层及沉陷阶段地热储盖组合关系（据文献[26-27]修改）

Figure 1. Stratigraphic column and subsidence-stage-specific geothermal-reservoir–seal assemblages in the Songliao Basin

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图 2 松辽盆地沉陷阶段主要地层砂体厚度等值线图

Figure 2. Contour map of net sandstone thickness within the dominant stratigraphic units for the subsidence stage, Songliao Basin

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图 3 松辽盆地沉陷阶段主要热储孔隙度与渗透率分布特征

Figure 3. Porosity and permeability distributions of the preincipal geothermal reservoirs during the subsidence stage in the Songliao Basin

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图 4 3段式黄金分割法示意图

Figure 4. Schematic of the tripartite golden-section method

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图 5 砂体厚度、孔隙度和渗透率频率分布直方图及累计概率百分比图

Figure 5. Histograms of Frequency distribution and cumulative probability curves for sandstone thickness, porosity, and permeability

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图 6 回归标准化残差的频率分布直方图(a)和正态P−P图(b)

Figure 6. Frequency histogram (a) and normal P–P plot (b) of standardized regression residuals

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图 7 回归标准化残差图

Figure 7. Standardized residual plot of the regression

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图 8 分级赋值−权重法热储评价结果

Figure 8. Geothermal reservoir assessment results based on the hierarchical grading–weighting method

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表 1 砂体厚度、孔隙度、渗透率评价标准

Table 1. Evaluation criteria for sandstone thickness, porosity and permeability

参数	类别	概率累计百分比/%	黄金分割数/个	实际个数/个	黄金分割比例/%	评价标准
砂体厚度	Ⅰ类	13	40	36	14.6	>60 m
	Ⅱ类	23	65	67	23.6	[30，60] m
	Ⅲ类	64	171	174	61.8	<30 m
孔隙度	Ⅰ类	16	33	36	14.6	<17%
	Ⅱ类	24	54	55	23.6	[17%，23%]
	Ⅲ类	60	140	136	61.8	>23%
渗透率	Ⅰ类	15	36	38	14.6	>65×10⁻³ μm²
	Ⅱ类	21	58	51	23.6	[15，65]×10⁻³ μm²
	Ⅲ类	64	152	157	61.8	<15×10⁻³ μm²

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表 2 松辽盆地部分地热田热储参数（据文献[30-32]修改）

Table 2. Geothermal reservoir parameters of selected geothermal fields in the Songliao Basin

地热田	编号	砂体厚度		孔隙度		渗透率		日产水量
地热田	编号	数值/m	归一化值	数值/%	归一化值	数值/10⁻³ μm²	归一化值	数值/(t·d⁻¹)	归一化值
大庆东风	1	2.60	0.013	25.00	0.833	136.71	0.169	25.26	0.023
	2	3.80	0.019	17.00	0.567	0.46	0.001	0.07	0.000
	3	4.00	0.020	25.00	0.833	224.03	0.278	26.58	0.024
	4	4.00	0.020	26.00	0.867	278.33	0.345	29.97	0.027
	5	4.40	0.022	25.00	0.833	136.71	0.169	17.41	0.016
	6	4.80	0.024	26.50	0.883	359.40	0.445	55.09	0.050
	7	5.40	0.027	26.50	0.883	359.40	0.445	167.75	0.153
	8	6.00	0.030	22.00	0.733	16.20	0.020	7.60	0.007
	9	7.60	0.038	24.00	0.800	163.47	0.202	28.95	0.026
	10	10.80	0.054	24.00	0.800	163.47	0.202	57.53	0.053
	11	12.60	0.063	20.30	0.677	4.84	0.006	6.97	0.006
	12	16.00	0.080	26.00	0.867	807.29	1.000	245.56	0.224
	13	20.00	0.100	27.00	0.900	302.73	0.375	557.63	0.509
	14	25.60	0.127	23.40	0.780	43.83	0.054	61.17	0.056
	15	26.00	0.129	22.00	0.733	25.90	0.032	63.85	0.058
	16	26.60	0.132	25.00	0.833	136.71	0.169	391.03	0.357
	17	34.20	0.170	16.00	0.533	4.69	0.006	4.30	0.004
	18	39.80	0.198	22.00	0.733	25.90	0.032	60.20	0.055
	19	43.60	0.217	24.50	0.817	191.37	0.237	264.43	0.242
	20	48.00	0.239	24.50	0.817	191.37	0.237	179.54	0.164
	21	49.00	0.244	25.50	0.850	262.26	0.325	353.97	0.323
	22	49.80	0.248	21.50	0.717	22.46	0.028	99.15	0.091
	23	50.60	0.252	21.00	0.700	19.48	0.024	66.15	0.060
	24	52.80	0.263	24.00	0.800	45.75	0.057	395.78	0.361
	25	54.80	0.273	25.00	0.833	136.71	0.169	440.60	0.402
	26	74.60	0.371	25.00	0.833	60.82	0.075	598.95	0.547
	27	82.60	0.411	17.50	0.583	7.19	0.009	24.76	0.023
	28	2.30	0.011	17.00	0.567	1.23	0.002	30.66	0.028
	29	3.20	0.016	21.00	0.700	21.66	0.027	2.10	0.002
	30	6.40	0.032	25.20	0.840	254.89	0.316	83.13	0.076
	31	6.40	0.032	22.00	0.733	13.33	0.017	0.92	0.001
	32	7.20	0.036	21.25	0.708	24.20	0.030	48.51	0.044
	33	7.42	0.037	22.20	0.740	110.30	0.137	22.42	0.020
	34	8.60	0.043	19.80	0.660	12.70	0.016	25.69	0.023
	35	8.60	0.043	21.80	0.727	12.12	0.015	1.82	0.002
	36	9.00	0.045	20.00	0.667	59.68	0.074	6.64	0.006
	37	9.60	0.048	30.00	0.950	640.49	0.793	230.00	0.210
	38	12.20	0.061	17.70	0.590	31.40	0.039	0.68	0.001
	39	12.60	0.063	23.66	0.789	165.81	0.205	57.53	0.053
	40	14.20	0.071	27.00	0.900	421.33	0.522	228.51	0.209
	41	15.40	0.077	27.50	0.917	484.45	0.600	222.94	0.204
	42	16.60	0.083	14.60	0.487	0.39	0.000	24.47	0.022
	43	17.20	0.086	19.00	0.633	45.14	0.056	21.16	0.019
	44	19.60	0.098	22.43	0.748	117.62	0.146	28.13	0.026
	45	21.40	0.106	19.04	0.635	9.05	0.011	10.34	0.009
	46	21.60	0.107	18.40	0.613	6.81	0.008	0.57	0.001
	47	22.20	0.110	17.40	0.580	28.88	0.036	4.52	0.004
	48	22.60	0.112	21.87	0.729	100.59	0.125	77.02	0.070
	49	26.80	0.133	19.90	0.663	4.90	0.006	4.24	0.004
	50	27.20	0.135	25.20	0.840	254.89	0.316	437.51	0.400
	51	27.60	0.137	19.61	0.654	53.52	0.066	34.72	0.032
	52	27.60	0.137	26.40	0.880	108.86	0.135	100.93	0.092
	53	28.60	0.142	23.80	0.793	31.48	0.039	24.62	0.022
	54	29.80	0.148	21.45	0.715	89.46	0.111	161.84	0.148
	55	30.20	0.150	22.60	0.753	123.33	0.153	111.64	0.102
	56	30.20	0.150	17.12	0.571	26.70	0.033	3.64	0.003
	57	30.30	0.151	17.94	0.598	5.55	0.007	0.10	0.000
	58	31.40	0.156	22.84	0.761	49.11	0.061	1.70	0.002
杜蒙	59	32.20	0.160	11.20	0.373	0.28	0.000	0.50	0.000
	60	32.40	0.161	22.25	0.742	37.77	0.047	40.46	0.037
	61	33.00	0.164	25.36	0.845	266.54	0.330	365.92	0.334
	62	33.20	0.165	24.33	0.811	199.92	0.248	255.55	0.233
	63	34.00	0.169	16.60	0.553	3.06	0.004	4.69	0.004
	64	36.60	0.182	22.30	0.743	15.39	0.019	62.08	0.057
	65	38.00	0.189	21.85	0.728	12.41	0.015	13.61	0.012
	66	38.80	0.193	22.57	0.752	122.30	0.151	98.37	0.090
	67	40.60	0.202	21.74	0.725	30.10	0.037	38.73	0.035
	68	42.80	0.213	21.30	0.710	9.55	0.012	96.28	0.088
	69	53.90	0.268	20.80	0.693	19.81	0.025	8.68	0.008
	70	55.00	0.274	19.58	0.653	4.20	0.005	15.79	0.014
	71	57.20	0.285	24.67	0.822	219.83	0.272	615.59	0.562
	72	58.40	0.291	22.96	0.765	51.80	0.064	183.36	0.167
	73	64.80	0.322	23.51	0.784	66.16	0.082	235.94	0.215
	74	86.20	0.429	18.40	0.613	2.39	0.003	45.49	0.042
	75	92.00	0.458	25.70	0.857	175.30	0.217	699.71	0.639
林甸	76	103.20	0.513	16.28	0.543	2.65	0.003	93.19	0.085
	77	105.80	0.526	18.88	0.629	8.43	0.010	2.04	0.002
	78	134.20	0.668	20.70	0.690	18.95	0.023	277.67	0.254
	79	28.60	0.142	20.00	0.667	22.10	0.027	25.06	0.023
	80	40.00	0.199	24.00	0.800	117.32	0.145	447.49	0.409
	81	40.80	0.203	25.00	0.833	443.19	0.549	144.33	0.132
	82	41.20	0.205	23.00	0.767	65.15	0.081	45.23	0.041
	83	42.40	0.211	23.00	0.767	133.57	0.165	105.57	0.096
	84	42.60	0.212	23.05	0.768	67.09	0.083	189.99	0.174
	85	44.40	0.221	25.50	0.850	598.15	0.741	161.81	0.148
	86	47.80	0.238	23.00	0.767	133.57	0.165	116.71	0.107
	87	48.80	0.243	16.00	0.533	2.01	0.002	4.49	0.004
	88	50.60	0.252	26.00	0.867	380.52	0.471	388.54	0.355
	89	50.60	0.252	23.00	0.767	65.15	0.081	170.49	0.156
	90	52.80	0.263	26.00	0.867	380.52	0.471	396.05	0.362
	91	53.60	0.267	26.00	0.867	380.52	0.471	100.35	0.092
	92	54.30	0.270	25.50	0.850	195.06	0.242	277.53	0.253
	93	56.20	0.280	25.00	0.833	211.29	0.262	242.69	0.222
	94	56.40	0.281	25.00	0.833	211.29	0.262	265.35	0.242
	95	57.50	0.286	26.00	0.867	380.52	0.471	316.92	0.289
	96	58.20	0.290	25.00	0.833	211.29	0.262	151.26	0.138
	97	59.40	0.296	19.00	0.633	12.13	0.015	20.83	0.019
	98	60.40	0.300	13.00	0.433	0.33	0.000	0.78	0.001
	99	64.60	0.321	26.50	0.883	510.66	0.633	174.07	0.159
	100	66.00	0.328	22.00	0.733	73.33	0.091	64.76	0.059
	101	66.60	0.331	24.50	0.817	157.45	0.195	235.02	0.215
	102	67.80	0.337	25.00	0.833	136.71	0.169	247.22	0.226
	103	68.80	0.342	22.00	0.733	36.17	0.045	235.02	0.215
	104	77.10	0.384	18.00	0.600	6.66	0.008	8.51	0.008
	105	85.00	0.423	20.00	0.667	22.10	0.027	152.56	0.139
	106	87.00	0.433	24.00	0.800	67.15	0.083	281.47	0.257
	107	97.60	0.486	19.00	0.633	12.13	0.015	17.07	0.016
	108	108.00	0.537	26.00	0.867	278.33	0.345	619.67	0.566
	109	114.00	0.567	22.50	0.750	23.11	0.029	17.06	0.016
	110	115.80	0.576	23.00	0.767	32.98	0.041	243.59	0.222
	111	120.60	0.600	24.00	0.800	67.15	0.083	547.90	0.500
	112	130.20	0.648	24.50	0.817	95.81	0.119	511.80	0.467
	113	142.80	0.710	26.50	0.883	397.14	0.492	810.46	0.740
	114	146.80	0.730	27.00	0.900	566.66	0.702	1094.89	1.000
	115	155.80	0.775	25.00	0.833	136.71	0.169	734.23	0.671
	116	160.40	0.798	26.00	0.867	278.33	0.345	590.05	0.539
	117	176.00	0.876	23.00	0.767	32.98	0.041	508.95	0.465
	118	201.00	1.000	22.00	0.733	16.20	0.020	300.39	0.274

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表 3 日产水量与特征参数相关性分析

Table 3. Correlation analysis between daily water yield and characteristic parameters

		日产水量	砂体厚度	孔隙度	渗透率
日产水量	皮尔逊相关系数	1	0.590	0.571	0.455
	显著性sig.值	/	0.000	0.000	0.000
	个案数	118	118	118	118
砂体厚度	皮尔逊相关系数	/	1	0.085	−0.026
	显著性sig.值	/	/	0.358	0.776
	个案数	/	118	118	118
孔隙度	皮尔逊相关系数	/	/	1	0.712
	显著性sig.值	/	/	/	0.000
	个案数	/	/	118	118
渗透率	皮尔逊相关系数	/	/	/	1
	显著性sig.值	/	/	/	/
	个案数	/	/	/	118

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表 4 线性回归分析模型及其评价

Table 4. Linear regression analysis models and their assessment

模型	干扰项ε与自变量X	未标准化系数		标准化系数	t检验	显著性sig.值	共线性诊断		相关系数 R	决定系数 R²	调整后 R²	标准估算误差
模型	干扰项ε与自变量X	回归系数	标准误差	标准化系数	t检验	显著性sig.值	容差	方差膨胀因子	相关系数 R	决定系数 R²	调整后 R²	标准估算误差
1	ε	0.024	0.022	/	1.116	0.267	/	/	0.590	0.348	0.342	0.152
1	H	0.548	0.070	0.590	7.866	0.000	1.000	1	0.590	0.348	0.342	0.152
2	ε	−0.566	0.097	/	−5.814	0.000	/	/	0.572	0.327	0.321	0.154
2	φ	0.966	0.129	0.572	7.503	0.000	1.000	1	0.572	0.327	0.321	0.154
3	ε	0.086	0.020	/	4.275	0.000	/	/	0.455	0.207	0.200	0.167
3	K	0.428	0.078	0.455	5.505	0.000	1.000	1	0.455	0.207	0.200	0.167
4	ε	−0.494	0.127	/	−3.896	0.000	/	/	0.576	0.331	0.320	0.154
	φ	0.849	0.184	0.502	4.623	0.000	0.493	2.029
	K	0.092	0.102	0.097	0.897	0.371	0.493	2.029
5	ε	−0.630	0.074	/	−8.546	0.000	/	/	0.788	0.621	0.615	0.116
	φ	0.887	0.097	0.525	9.116	0.000	0.993	1.007
	H	0.506	0.054	0.545	9.461	0.000	0.993	1.007
6	ε	−0.052	0.020	/	−2.535	0.013	/	/	0.755	0.570	0.562	0.124
	H	0.560	0.057	0.602	9.839	0.000	0.999	1.001
	K	0.443	0.058	0.471	7.695	0.000	0.999	1.001
7	ε	−0.485	0.093	/	−5.192	0.000	/	/	0.800	0.640	0.631	0.114
	K	0.185	0.076	0.197	2.443	0.016	0.485	1.023
	φ	0.648	0.137	0.383	4.734	0.000	0.482	2.057
	H	0.523	0.053	0.562	9.893	0.000	0.977	2.061

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表 5 方法1对应的砂岩热储厚度与物性参数评价标准及取值标准（参数取值标准据文献[9]）

Table 5. Evaluation criteria and quantitative value standards for sandstone geothermal storage thickness and petrophysical parameters under Method 1

评价分类	砂体厚度/m	孔隙度/%	渗透率/10⁻³ μm²	参数取值标准
Ⅰ类热储	>60	>23	>65	100
Ⅱ类热储	[30，60]	[17，23]	[15，65]	[20，100)
Ⅲ类热储	<30	<17	<15	[10，20)

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表 6 方法2和方法3对应的砂岩热储厚度与物性参数评价标准及取值标准（据文献[9]修改）

Table 6. Evaluation criteria and quantitative value standards for sandstone geothermal-reservoir thickness and petrophysical parameters under Method 2 and Method 3

评价分类	砂体厚度H/m	孔隙度φ/%	渗透率K/10⁻³ μm²	参数取值标准
Ⅰ类热储	≥100	≥25	≥500	100
Ⅱ类热储	(100，20]	(25，15]	(500，100]	[20，100）
Ⅲ类热储	<20	<15	<100	[10, 20）

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表 7 方法2和方法3对应的砂岩热储温度评价标准及取值标准（据文献[9]修改）

Table 7. Temperature-based evaluation criteria and value standards for sandstone geothermal reservoirs under Method 2 and Method 3

评价分类	温度中部温度T/℃	参数取值标准
Ⅰ类热储	≥150	100
Ⅱ类热储	[120，150)	100
Ⅱ类热储	[90，120)	[70, 90）
Ⅲ类热储	[30，90)	[10，70）

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表 8 3种评价方法评价结果对比

Table 8. Comparison of evaluation results from three assessment methods

评价单元编号	方法1 (H，K，φ)			方法2 (H，T，K，φ)			方法3 (T，K，φ)			方法1与方法2 评价得分排名差异的绝对值	方法2与方法3 评价得分排名差异的绝对值	方法3与方法1 评价得分排名差异的绝对值
评价单元编号	得分	排名	评价分类	得分	排名	评价分类	得分	排名	评价分类	方法1与方法2 评价得分排名差异的绝对值	方法2与方法3 评价得分排名差异的绝对值	方法3与方法1 评价得分排名差异的绝对值
qn3-2	129.66	1	Ⅰ	45.28	2	Ⅰ	34.77	8	Ⅰ	1	6	7
qn3-1	127.72	2	Ⅰ	46.43	1	Ⅰ	40.14	4	Ⅰ	1	3	2
qn1-3	124.26	3	Ⅰ	40.65	4	Ⅰ	35.10	7	Ⅰ	1	3	4
q3-1	123.66	4	Ⅰ	38.75	9	Ⅰ	31.39	12	Ⅰ	5	3	8
qn2-1	110.58	5	Ⅰ	40.38	5	Ⅰ	32.02	10	Ⅰ	0	5	5
qn3-3	107.08	6	Ⅰ	44.05	3	Ⅰ	45.25	1	Ⅰ	3	2	5
y2+3-4	106.94	7	Ⅰ	37.72	11	Ⅰ	36.82	5	Ⅰ	4	6	2
y2+3-2	106.29	8	Ⅰ	37.32	12	Ⅰ	36.45	6	Ⅰ	4	6	2
y1-3	104.15	9	Ⅰ	40.15	6	Ⅰ	40.73	3	Ⅰ	3	3	6
qn3-6	101.80	10	Ⅰ	38.05	10	Ⅰ	29.10	16	Ⅱ	0	6	6
y1-2	100.25	11	Ⅰ	39.49	8	Ⅰ	40.90	2	Ⅰ	3	6	9
y1-4	99.09	12	Ⅰ	29.70	28	Ⅱ	26.37	27	Ⅱ	16	1	15
qn3-4	96.63	13	Ⅰ	31.10	22	Ⅱ	28.08	19	Ⅱ	9	3	6
qn1-1	93.78	14	Ⅰ	39.50	7	Ⅰ	32.36	9	Ⅰ	7	2	5
qn3-8	93.78	15	Ⅱ	26.31	49	Ⅲ	18.82	70	Ⅲ	34	21	55
q4-1	92.53	16	Ⅱ	28.99	34	Ⅱ	26.58	25	Ⅱ	18	9	9
y2+3-1	85.17	17	Ⅱ	28.35	38	Ⅲ	31.32	13	Ⅰ	21	25	4
qn2-3	83.28	18	Ⅱ	35.66	13	Ⅰ	27.79	20	Ⅱ	5	7	2
qn1-2	83.12	19	Ⅱ	24.88	52	Ⅲ	28.40	18	Ⅱ	33	34	1
qn2-2	81.79	20	Ⅱ	35.47	14	Ⅰ	26.59	24	Ⅱ	6	10	4
q3-4	80.64	21	Ⅱ	33.71	17	Ⅱ	26.32	28	Ⅱ	4	11	7
q4-2	79.76	22	Ⅱ	29.24	31	Ⅱ	21.67	48	Ⅲ	9	17	26
q4-3	78.34	23	Ⅱ	30.14	25	Ⅱ	29.66	14	Ⅰ	2	11	9
qn2-5	76.85	24	Ⅱ	31.71	20	Ⅱ	26.74	23	Ⅱ	4	3	1
q4-4	75.32	25	Ⅱ	32.95	18	Ⅱ	25.41	31	Ⅱ	7	13	6
q3-6	72.25	26	Ⅱ	34.03	16	Ⅱ	26.76	22	Ⅱ	10	6	4
y1-1	69.89	27	Ⅱ	30.97	23	Ⅱ	29.58	15	Ⅱ	4	8	12
q4-5	68.95	28	Ⅱ	30.00	26	Ⅱ	22.43	40	Ⅲ	2	14	12
q3-3	68.03	29	Ⅱ	29.61	29	Ⅱ	22.26	43	Ⅲ	0	14	14
q3-2	67.97	30	Ⅱ	34.06	15	Ⅱ	24.59	32	Ⅱ	15	17	2
q4-9	67.68	31	Ⅱ	28.39	37	Ⅱ	20.84	53	Ⅲ	6	16	22
qn2-4	66.85	32	Ⅱ	30.56	24	Ⅱ	22.98	37	Ⅱ	8	13	5
qn2-8	66.40	33	Ⅱ	29.06	33	Ⅱ	21.49	49	Ⅲ	0	16	16
qn2-7	66.23	34	Ⅱ	29.44	30	Ⅱ	21.87	46	Ⅲ	4	16	12
qn1-7	65.74	35	Ⅱ	30.00	27	Ⅱ	22.42	41	Ⅲ	8	14	6
y2+3-3	65.63	36	Ⅱ	31.38	21	Ⅱ	26.54	26	Ⅱ	15	5	10
q3-5	65.57	37	Ⅱ	32.54	19	Ⅱ	29.05	17	Ⅱ	18	2	20
y2+3-5	65.06	38	Ⅲ	21.70	65	Ⅲ	22.30	42	Ⅲ	27	23	4
qn1-6	64.34	39	Ⅲ	27.79	41	Ⅲ	20.25	58	Ⅲ	2	17	19
qn2-6	63.72	40	Ⅲ	28.17	40	Ⅲ	20.62	54	Ⅲ	0	14	14
q3-11	63.39	41	Ⅲ	28.22	39	Ⅲ	18.57	72	Ⅲ	2	33	31
q4-12	63.17	42	Ⅲ	26.67	45	Ⅲ	19.17	65	Ⅲ	3	20	23
q4-10	62.47	43	Ⅲ	28.53	36	Ⅱ	20.97	52	Ⅲ	7	16	9
q4-11	62.47	44	Ⅲ	23.99	54	Ⅲ	16.65	85	Ⅲ	10	31	41
q3-8	62.00	45	Ⅲ	27.24	43	Ⅲ	23.62	33	Ⅱ	2	10	12
q4-6	61.21	46	Ⅲ	26.57	47	Ⅲ	19.07	68	Ⅲ	1	21	22
qn1-8	61.21	47	Ⅲ	25.71	51	Ⅲ	18.25	75	Ⅲ	4	24	28
qn3-9	53.95	48	Ⅲ	25.81	50	Ⅲ	21.30	50	Ⅲ	2	0	2
qn3-5	50.55	49	Ⅲ	27.46	42	Ⅲ	23.14	35	Ⅱ	7	7	14
qn1-4	49.35	50	Ⅲ	28.68	35	Ⅱ	31.70	11	Ⅰ	15	24	39
y1-5	49.27	51	Ⅲ	29.21	32	Ⅱ	27.10	21	Ⅱ	19	11	30
y2+3-6	48.74	52	Ⅲ	19.33	76	Ⅲ	19.25	63	Ⅲ	24	13	11
qn1-5	47.00	53	Ⅲ	21.15	69	Ⅲ	20.30	57	Ⅲ	16	12	4
qn1-9	45.93	54	Ⅲ	27.18	44	Ⅲ	22.82	38	Ⅲ	10	6	16
qn3-11	45.93	55	Ⅲ	23.06	60	Ⅲ	18.33	74	Ⅲ	5	14	19
q4-8	44.64	56	Ⅲ	26.51	48	Ⅲ	22.04	44	Ⅲ	8	4	12
q4-15	43.02	57	Ⅲ	23.75	56	Ⅲ	25.43	30	Ⅱ	1	26	27
qn3-10	40.62	58	Ⅲ	21.64	66	Ⅲ	20.06	59	Ⅲ	8	7	1
q4-7	40.29	59	Ⅲ	23.95	55	Ⅲ	19.27	62	Ⅲ	4	7	3
qn1-10	39.42	60	Ⅲ	23.26	59	Ⅲ	21.79	47	Ⅲ	1	12	13
qn3-7	38.79	61	Ⅲ	22.81	61	Ⅲ	18.43	73	Ⅲ	0	12	12
q3-17	38.43	62	Ⅲ	22.22	64	Ⅲ	18.75	71	Ⅲ	2	7	9
q3-10	37.38	63	Ⅲ	26.59	46	Ⅲ	25.46	29	Ⅱ	17	17	34
qn1-11	35.83	64	Ⅲ	23.27	58	Ⅲ	19.31	61	Ⅲ	6	3	3
q3-9	35.55	65	Ⅲ	24.61	53	Ⅲ	21.17	51	Ⅲ	12	2	14
qn2-13	33.02	66	Ⅲ	13.58	92	Ⅲ	11.27	93	Ⅲ	26	1	27
q3-19	31.07	67	Ⅲ	19.49	72	Ⅲ	16.36	87	Ⅲ	5	15	20
q3-16	28.22	68	Ⅲ	19.47	73	Ⅲ	20.00	60	Ⅲ	5	13	8
q3-18	28.09	69	Ⅲ	21.63	67	Ⅲ	23.08	36	Ⅱ	2	31	33
q4-14	27.47	70	Ⅲ	23.55	57	Ⅲ	20.53	56	Ⅲ	13	1	14
qn2-10	23.87	71	Ⅲ	18.92	79	Ⅲ	15.62	89	Ⅲ	8	10	18
q3-15	23.86	72	Ⅲ	15.78	89	Ⅲ	16.58	86	Ⅲ	17	3	14
q3-12	23.70	73	Ⅲ	20.84	70	Ⅲ	22.64	39	Ⅲ	3	31	34
q4-16	23.41	74	Ⅲ	22.69	62	Ⅲ	20.54	55	Ⅲ	12	7	19
q3-26	23.25	75	Ⅲ	20.30	71	Ⅲ	18.89	69	Ⅲ	4	2	6
y1-6	22.72	76	Ⅲ	18.65	80	Ⅲ	18.22	76	Ⅲ	4	4	0
y1-8	22.72	77	Ⅲ	14.57	91	Ⅲ	13.11	91	Ⅲ	14	0	14
q3-14	22.52	78	Ⅲ	16.71	88	Ⅲ	14.78	90	Ⅲ	10	2	12
q3-7	22.10	79	Ⅲ	22.63	63	Ⅲ	23.59	34	Ⅱ	16	29	45
q3-27	22.10	80	Ⅲ	19.38	75	Ⅲ	19.18	64	Ⅲ	5	11	16
q3-20	21.81	81	Ⅲ	12.07	94	Ⅲ	11.19	94	Ⅲ	13	0	13
y1-7	21.79	82	Ⅲ	21.27	68	Ⅲ	22.03	45	Ⅲ	14	23	37
qn1-12	21.59	83	Ⅲ	17.11	87	Ⅲ	17.94	77	Ⅲ	4	10	6
qn1-13	21.37	84	Ⅲ	19.21	78	Ⅲ	19.14	66	Ⅲ	6	12	18
q3-24	20.28	85	Ⅲ	15.44	90	Ⅲ	17.84	78	Ⅲ	5	12	7
q3-21	20.11	86	Ⅲ	18.46	81	Ⅲ	16.33	88	Ⅲ	5	7	2
q3-25	19.59	87	Ⅲ	19.31	77	Ⅲ	19.09	67	Ⅲ	10	10	20
q3-23	19.59	88	Ⅲ	17.75	83	Ⅲ	17.06	81	Ⅲ	5	2	7
q3-22	19.59	89	Ⅲ	17.52	85	Ⅲ	16.76	83	Ⅲ	4	2	6
q3-13	19.59	90	Ⅲ	8.97	95	Ⅲ	6.87	95	Ⅲ	5	0	5
q4-13	19.48	91	Ⅲ	19.39	74	Ⅲ	17.30	80	Ⅲ	17	6	11
qn1-15	19.03	92	Ⅲ	17.48	86	Ⅲ	16.72	84	Ⅲ	6	2	8
qn2-12	17.80	93	Ⅲ	8.66	96	Ⅲ	5.85	96	Ⅲ	3	0	3
qn1-14	16.52	94	Ⅲ	17.66	84	Ⅲ	16.94	82	Ⅲ	10	2	12
qn2-11	16.52	95	Ⅲ	13.40	93	Ⅲ	11.72	92	Ⅲ	2	1	3
qn2-9	16.17	96	Ⅲ	17.95	82	Ⅲ	17.60	79	Ⅲ	14	3	17
标准差	30.85	/	/	7.98	/	/	7.07	/	/	/	/	/
绝对值之和	/	/	/	/	/	/	/	/	/	772	1002	1262

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