WO2021232924A1 - 一种考虑温度效应的深层-超深层岩石力学参数预测方法 - Google Patents

一种考虑温度效应的深层-超深层岩石力学参数预测方法 Download PDF

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WO2021232924A1
WO2021232924A1 PCT/CN2021/081981 CN2021081981W WO2021232924A1 WO 2021232924 A1 WO2021232924 A1 WO 2021232924A1 CN 2021081981 W CN2021081981 W CN 2021081981W WO 2021232924 A1 WO2021232924 A1 WO 2021232924A1
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deep
temperature
rock mechanics
ultra
target
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鞠玮
张辉
徐珂
申建
吴财芳
秦勇
杨兆彪
沈玉林
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中国矿业大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/20—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by using diffraction of the radiation by the materials, e.g. for investigating crystal structure; by using scattering of the radiation by the materials, e.g. for investigating non-crystalline materials; by using reflection of the radiation by the materials
    • G01N23/207—Diffractometry using detectors, e.g. using a probe in a central position and one or more displaceable detectors in circumferential positions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/02—Details not specific for a particular testing method
    • G01N2203/0202—Control of the test
    • G01N2203/0212—Theories, calculations
    • G01N2203/0218—Calculations based on experimental data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
    • G01N2203/02—Details not specific for a particular testing method
    • G01N2203/022—Environment of the test
    • G01N2203/0222—Temperature
    • G01N2203/0226—High temperature; Heating means

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  • the invention relates to a method for predicting mechanical parameters, which is especially suitable for the fields of oil and gas development geology and rock mechanics.
  • Rock mechanics parameters can be obtained through indoor core sample experiments, which are static values of rock mechanics, which can be referenced; they can also be estimated and obtained based on geophysical logging data. They are dynamic values of rock mechanics, with certain deviations, which are generally required. Dynamic and static conversion of rock mechanics parameters for correction.
  • the deep-ultra-deep rock is in a certain geothermal environment, and the rock undergoes microscopic changes under the temperature effect, which affects the macroscopic rock mechanical properties.
  • the rock mechanics parameters directly measured by standard size cores under normal temperature conditions obtained in the laboratory can no longer meet the requirements of actual conditions. For this reason, it is necessary to carry out the rock mechanical property test under the temperature effect.
  • the invention patent with application publication number CN104122149A proposes a method for measuring rock mechanics under different temperature conditions by gradually increasing the temperature using a single piece of core specimen, in an attempt to solve the problem that the rock mechanics parameter experiment target core is scarce.
  • the experimental operation obtains the rock mechanics parameters under different temperature conditions and the reliability of the measured data.
  • the invention with application publication number CN105259036A proposes a method for measuring stratum rock mechanics parameters, hoping to avoid the influence of heterogeneous rock core mechanical properties to the greatest extent and maximize the core utilization.
  • the present invention provides a method for predicting deep-ultra-deep rock mechanics parameters with simple steps and high reliability considering temperature effects.
  • the core of the method is to establish the rock mechanics parameters before and after the temperature difference loading path. The correlation between.
  • the method for predicting the rock mechanics parameters of the deep-ultra-deep layer in consideration of the temperature effect of the present invention has the following steps:
  • Step 1 Carry out fine regional geological survey and geophysical exploration, find out the age, burial depth and temperature characteristics of the target layer, and calculate the ratio of the temperature rise and fall rate extracted to the core of the target layer on the surface;
  • Step 2 Collect multiple fresh samples of the target layer that have not experienced deep-ultra-deep burial, and the number of collections is determined by the target temperature level, which is recorded as A series samples; collect the same target layer that has experienced deep-ultra-deep burial Drilling core samples of different depths are recorded as B series samples; then all samples are processed into rock mechanics test samples, and the mineral composition and content of each sample are tested;
  • Step 3 According to the experimental test results of step 2, select the sample with the mineral composition and content closest to the B series sample from the A series sample, which is marked as the C series sample, and the labels are C1, C2, ⁇ , Cn;
  • Step 4 Heat the even-numbered samples of the first, second, ⁇ and m-bit samples in the C series obtained in step 3 to the target temperature T1, T2, ⁇ , and Tm at a rate of v1 respectively, and then keep the temperature for 2h, and then set the temperature in the corresponding Carry out rock mechanics experiments at the target temperature to obtain the rock mechanics parameter S set under different target temperature conditions, denoted as L1(x1,x2, ⁇ ,xk), L2(x1,x2, ⁇ ,xk), ⁇ ⁇ , Lm(x1, x2, ⁇ , xk), where x1, x2, ⁇ , xk are different rock mechanics parameters;
  • Step 5 After the first, second, ..., m odd-numbered samples in the C series obtained in step 3 are heated to the target temperature T1, T2, ..., Tm at the same very slow rate v1 in step 4 Constant temperature for 2h, then all odd-numbered samples of the C series are cooled to room temperature T0 at a very fast rate v2, and finally rock mechanics experiments are carried out at temperature T0 to obtain the rock mechanics parameter S'set under different target temperature conditions, denoted as L'1 (x1, x2, ⁇ , xk), L'2 (x1, x2, ⁇ , xk), ⁇ , L'm(x1, x2, ⁇ , xk), where x1, x2, ⁇ , xk are different rock mechanics parameters;
  • Step 7 Perform rock mechanics experiments under room temperature T0 on the B series samples obtained in Step 2, and the obtained rock mechanics is the S’ set of the drilling core of the target layer under deep-ultra-deep conditions;
  • Step 8 Combining step 1 to obtain the target's deep-ultra-deep layer temperature, temperature rise and fall rate ratio, and the target layer drilling core rock mechanics parameter set S'set under the deep-ultra-deep layer conditions obtained in step 7 and substitute the function obtained in step 6
  • step 1 above it is preferable to determine the age and burial depth of the target layer based on 3D seismic fine interpretation; the temperature characteristics of the target layer are obtained from formation tests; the heating rate is the ratio of the temperature of the target layer to its age; the cooling rate is the temperature of the target layer and The ratio of the time to rise to the surface; the rate of temperature rise and fall is the ratio of the rate of temperature rise to the rate of temperature drop.
  • the number of A series samples is not less than 20 pieces, and the size of each piece should be greater than 10cm ⁇ 10cm ⁇ 10cm;
  • the B sample is a plunger sample with a diameter of 2.5cm and a length of more than 8cm;
  • the sample is plunger-shaped with a diameter of 2.5cm and a height of 5cm;
  • the mineral composition and content of the sample are obtained by X-ray diffraction experiments;
  • the deep layer is 4500-6000m deep, and the ultra-deep layer is more than 6000m deep.
  • the rate v1 is 0.01°C/min, and the rate v2 is 1°C/min.
  • the target temperature T1, T2,..., Tm is 40°C, 60°C, 80°C, 100°C, 120°C, 140°C, 160°C, 180°C, 200°C and 220 °C, room temperature T0 is 20°C.
  • the rock mechanics parameters obtained by drilling cores in the laboratory are actually the values after the rock has undergone "rapid heating and then rapid cooling". It’s just a pure experiment with core samples taken from deep underground, without considering that the core taken from deep underground has actually undergone a process of slow heating and extraction to the surface of the surface. This process has had an impact on the mechanical properties of the rock. The impact. Therefore, if the rock mechanics experiment is carried out directly using deep-ultra-deep drilling cores, the obtained rock mechanics parameters must be obviously different from the actual situation.
  • the purpose of the present invention is to provide a method for predicting deep-ultra-deep rock mechanical parameters considering the temperature effect.
  • the method predicts the deep-ultra-deep rock mechanical parameters by establishing the correlation between the rock mechanical parameters before and after the temperature difference loading path , Its steps are simple, the effect is good, and the measurement results are highly reliable.
  • Step 1 Carry out fine regional geological survey and geophysical exploration to find out the age, burial depth and temperature characteristics of the target layer, and calculate the ratio of temperature rise and fall to the core of the target layer on the surface; determine the age of the target layer based on the fine interpretation of 3D seismic And burial depth; the temperature characteristics of the target layer are obtained from formation testing; the heating rate is the ratio of the temperature of the target layer to its age; the cooling rate is the ratio of the temperature of the target layer to the time it rises to the surface; the temperature rise and fall rate ratio is the ratio of the heating rate and the cooling rate ratio;
  • Step 2 Collect multiple fresh samples of the target layer that have not experienced deep-ultra-deep burial, and the number of collections is determined by the target temperature level, which is recorded as A series samples; collect the same target layer that has experienced deep-ultra-deep burial Drilling core samples of different depths are recorded as B series samples; then all samples are processed into rock mechanics test samples, and the mineral composition and content of each sample are tested; the number of A series samples is not less than 20 pieces, each The size of the piece should be greater than 10cm ⁇ 10cm ⁇ 10cm; sample B is a plunger-like sample with a diameter of 2.5cm and a length greater than 8cm; the rock mechanics test sample is a plunger-like sample with a diameter of 2.5cm and a height of 5cm; sample mineral composition And the content is obtained by X-ray diffraction experiment; the deep layer is 4500 ⁇ 6000m buried depth, and the ultra-deep layer is buried depth greater than 6000m;
  • Step 3 According to the experimental test results of step 2, select the sample with the mineral composition and content closest to the B series sample from the A series sample, which is marked as the C series sample, and the labels are C1, C2, ⁇ , Cn;
  • Step 4 For the first, second, ⁇ , and m even-numbered samples in the C series obtained in step 3, they are heated to the target temperature T1, T2, ⁇ , and Tm at a rate of v1, respectively, and then kept at a constant temperature for 2h.
  • the rate v1 is specifically 0.01°C/min, then carry out rock mechanics experiments at the corresponding target temperature to obtain the rock mechanics parameter S set under different target temperature conditions, denoted as L1(x1,x2, ⁇ ,xk), L2(x1,x2 , ⁇ ,Xk), ⁇ ,Lm(x1,x2, ⁇ ,xk), where x1, x2, ⁇ ,xk are different rock mechanics parameters;
  • Step 5 After the first, second, ..., m odd-numbered samples in the C series obtained in step 3 are heated to the target temperature T1, T2, ..., Tm at the same very slow rate v1 in step 4 Constant temperature for 2h, then all odd-numbered samples of C series are cooled to room temperature T0 at a very fast rate v2, rate v2 is 1°C/min, and finally rock mechanics experiments are carried out at temperature T0 to obtain rock mechanics parameters S under different target temperature conditions 'Set, denoted as L'1(x1,x2, ⁇ ,xk), L'2(x1,x2, ⁇ ,xk), ⁇ ,L'm(x1,x2, ⁇ , Xk), where x1, x2, ⁇ , xk are different rock mechanics parameters; target temperature T1, T2, ⁇ , Tm is 40°C, 60°C, 80°C, 100°C, 120°C, 140 °C, 160°C, 180°C, 200°C and 220°C,
  • Step 7 Carry out the rock mechanics experiment at room temperature T0 on the B series samples obtained in Step 2, and the rock mechanics obtained is the S'set of the drilling core of the target layer under deep-ultra-deep conditions; the room temperature T0 is 20°C;
  • Step 8 Combining step 1 to obtain the target's deep-ultra-deep layer temperature, temperature rise and fall rate ratio, and the target layer drilling core rock mechanics parameter set S'set under the deep-ultra-deep layer conditions obtained in step 7 and substitute the function obtained in step 6

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Abstract

一种考虑温度效应的深层-超深层岩石力学参数预测方法，适用于油气开发地质与岩石力学领域。取自深层-超深层的岩芯其实已经历了慢速升温、快速降温的过程，为消除其对岩石力学性质的影响，通过建立温度差异加载路径前后岩石力学参数之间的关联性，预测深层-超深层岩石力学参数，其步骤简单，效果好，测算结果可靠性高。

Description

一种考虑温度效应的深层-超深层岩石力学参数预测方法 技术领域
本发明涉及一种力学参数预测方法，尤其适用于油气开发地质与岩石力学领域，使用的一种考虑温度效应的深层-超深层岩石力学参数预测方法。
背景技术
准确预测岩石力学参数对于钻完井工程、油气开发方案与技术措施制定具有重要作用。岩石力学参数可以通过室内岩芯样品实验获取，为岩石力学静态值，其可参考性较高；也可以依据地球物理测井资料估算获取，为岩石力学动态值，存在着一定的偏差，一般需要岩石力学参数动静转换进行校正。
当前，伴随着油气勘探开发理论、技术和装备的突破发展，陆上深层-超深层已成为我国重要的勘探开发领域。油气勘探与资源评价结果显示，我国陆上深层-超深层领域油气资源丰富，截至2018年年底，国内深层-超深层累计天然气探明储量可达3.32×10 12m 3，主要集中于塔里木盆地和四川盆地。
深层-超深层岩石处于一定的地温场环境中，在温度效应下岩石发生微观变化，影响宏观岩石力学性质。在深层-超深层的复杂温度环境下，实验室获取的常温条件下利用标准尺寸岩芯直接测量出来的岩石力学参数已不能满足实际情况要求。为此，需要开展温度效应下的岩石力学性质测试。
申请公布号为CN104122149A的发明专利提出了一种利用单块岩芯试件通过逐级升温测量在不同温度条件下岩石力学的方法，试图解决在岩石力学参数实验目标岩芯稀缺条件下无法进行正常实验操作获取不同温度条件下岩石力学参数以及所测数据的可靠性问题。申请公布号为CN105259036A的发明提出了一种地层岩石力学参数的测量方法，希望可以最大程度地避免岩芯力学性质非均质的影响，并将岩芯利用最大化。
上述专利涉及的方法虽然开始考虑温度对岩石力学性质的影响，但都是直接利用获取的钻井岩芯在温度作用下测试岩石力学性质。然殊不知，采集实验样品的岩芯已经历埋藏时非常缓慢的升温与提升到地表非常快速的降温过程，岩石力学性质已然发生变化。在实验室内利用钻井岩芯获取的岩石力学参数其实是岩石经历“快速升温再快速降温”后的数值。用钻井岩芯直接开展岩石力学实验，获取的岩石力学参数与实际情况必然存在明显差异，对于深层-超深层岩石而言，误差更大。
发明内容
为了解决现有技术中存在的问题，本发明提供一种步骤简单、可靠性高的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其核心在于建立温度差异加载路径前后岩石力学参数之间的关联性。
为实现上述目标，本发明的考虑温度效应的深层-超深层岩石力学参数预测方法，其步骤如下：
步骤1，开展精细区域地质调查与地球物理勘探，查明目标层年代、埋藏深度和温度特征，并计算提取到地表目标层岩芯的升降温速率比；
步骤2，采集多个未经历深-超深埋藏作用的目标层新鲜试样，采集数量由目标温度级别确定，记为A系列试样；采集经历过深层-超深层埋藏作用的同一目标层内不同深度的钻井岩芯样品，记为B系列试样；然后将所有样品加工成岩石力学实验试样，并测试每个试样的矿物成分及含量；
步骤3，根据步骤2的实验测试结果，从A系列试样中优选矿物成分及含量与B系列试样最接近的试样，记为C系列试样，标号为C1，C2，···，Cn；
步骤4，对步骤3获取的C系列中第1，2，···，m位偶数试样以速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，然后在相应的目标温度下分别开展岩石力学实验，获取不同目标温度条件下岩石力学参数S集，记为L1(x1，x2，···，xk)，L2(x1，x2，···，xk)，···，Lm(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；
步骤5，对步骤3获取的C系列中第1，2，···，m位奇数试样以步骤4中同样非常慢的速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，然后C系列所有奇数试样再以非常快的速率v2降温到室温T0，最后在温度T0下开展岩石力学实验，获取不同目标温度条件下岩石力学参数S’集，记为L’1(x1，x2，···，xk)，L’2(x1，x2，···，xk)，···，L’m(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；
步骤6，基于步骤4和步骤5实验结果，构建岩石力学参数S集与S’集、升降温速率比u＝v1/v2、目标温度T之间的量化关系：Si＝f(S’i，u，Ti)(i＝1，2，···，m)；从而获得Si与S’、i、u和Ti之间的函数关系；
步骤7，对步骤2获取的B系列试样开展室温T0条件下的岩石力学实验，获取的岩石力学即为深层-超深层条件下目标层钻井岩芯的S’集；
步骤8，结合步骤1获取目标的深层-超深层温度、升降温速率比以及步骤7中获取的深层-超深层条件下目标层钻井岩芯岩石力学参数集S’集代入步骤6中获取的函数关系式：Si＝f(S’i，u，Ti)(i＝1，2，···，m)，从而获得深层-超深层条件下目标层岩石力学参数的预测值。
上述步骤1中优选的是，基于三维地震精细解释，确定目标层年代和埋藏深度情况；目标层温度特征由地层测试获取；升温速率为目标层温度与其年代之比；降温速率为目标层温度与提升至地表时间之比；升降温速率比为升温速率与降温速率的比值。
上述步骤2中优选的是，A系列样品数量不少于20件，每件的尺寸应大于10cm×10cm×10cm；B样品为柱塞状样品，直径2.5cm，长度大于8cm；岩石力学实验试样为柱塞状，直径为2.5cm，高 为5cm；试样矿物成分及含量利用X-射线衍射实验获取；深层为埋深4500～6000m，超深层为埋深大于6000m。
所述速率v1为0.01℃/min，速率v2为1℃/min。
上述步骤4和5中优选的是，目标温度T1，T2，···，Tm为40℃、60℃、80℃、100℃、120℃、140℃、160℃、180℃、200℃和220℃，室温T0为20℃。
有益效果：
目前在实验室内利用钻井岩芯获取的岩石力学参数其实是岩石经历“快速升温再快速降温”后的数值。只是纯粹的拿地下深处的岩芯样进行实验，没有考虑到取自地下深处的岩芯其实已经经历过了慢速升温、提取到地表快速升温的过程，这个过程已经对岩石力学性质产生了影响。因此单纯使用深层-超深层钻井岩芯直接开展岩石力学实验，获取的岩石力学参数与实际情况必然存在明显差异。
鉴于此，本发明的目的在于提供一种考虑温度效应的深层-超深层岩石力学参数预测方法，该方法通过建立温度差异加载路径前后岩石力学参数之间的关联性预测深层-超深层岩石力学参数，其步骤简单，效果好，测算结果可靠性高。
附图说明
图1本发明考虑温度效应的深层-超深层岩石力学参数预测方法的技术流程图
具体实施方式
下面结合附图对本发明的实施例做进一步说明
本发明的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其步骤如下：
步骤1，开展精细区域地质调查与地球物理勘探，查明目标层年代、埋藏深度和温度特征，并计算提取到地表目标层岩芯的升降温速率比；基于三维地震精细解释，确定目标层年代和埋藏深度情况；目标层温度特征由地层测试获取；升温速率为目标层温度与其年代之比；降温速率为目标层温度与提升至地表时间之比；升降温速率比为升温速率与降温速率的比值；
步骤2，采集多个未经历深-超深埋藏作用的目标层新鲜试样，采集数量由目标温度级别确定，记为A系列试样；采集经历过深层-超深层埋藏作用的同一目标层内不同深度的钻井岩芯样品，记为B系列试样；然后将所有样品加工成岩石力学实验试样，并测试每个试样的矿物成分及含量；A系列样品数量不少于20件，每件的尺寸应大于10cm×10cm×10cm；B样品为柱塞状样品，直径2.5cm，长度大于8cm；岩石力学实验试样为柱塞状，直径为2.5cm，高为5cm；试样矿物成分及含量利用X-射线衍射实验获取；深层为埋深4500～6000m，超深层为埋深大于6000m；
步骤3，根据步骤2的实验测试结果，从A系列试样中优选矿物成分及含量与B系列试样最接近的 试样，记为C系列试样，标号为C1，C2，···，Cn；
步骤4，对步骤3获取的C系列中第1，2，···，m个偶数试样以速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，速率v1具体为0.01℃/min，然后在相应的目标温度下分别开展岩石力学实验，获取不同目标温度条件下岩石力学参数S集，记为L1(x1，x2，···，xk)，L2(x1，x2，···，xk)，···，Lm(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；
步骤5，对步骤3获取的C系列中第1，2，···，m个奇数试样以步骤4中同样非常慢的速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，然后C系列所有奇数试样再以非常快的速率v2降温到室温T0，速率v2为1℃/min，最后在温度T0下开展岩石力学实验，获取不同目标温度条件下岩石力学参数S’集，记为L’1(x1，x2，···，xk)，L’2(x1，x2，···，xk)，···，L’m(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；目标温度T1，T2，···，Tm为40℃、60℃、80℃、100℃、120℃、140℃、160℃、180℃、200℃和220℃，
步骤6，基于步骤4和步骤5实验结果，构建岩石力学参数S集与S’集、升降温速率比u＝v1/v2、目标温度T之间的量化关系：Si＝f(S’i，u，Ti)(i＝1，2，···，m)；从而获得Si与S’、i、u和Ti之间的函数关系；
步骤7，对步骤2获取的B系列试样开展室温T0条件下的岩石力学实验，获取的岩石力学即为深层-超深层条件下目标层钻井岩芯的S’集；室温T0为20℃；
步骤8，结合步骤1获取目标的深层-超深层温度、升降温速率比以及步骤7中获取的深层-超深层条件下目标层钻井岩芯岩石力学参数集S’集代入步骤6中获取的函数关系式：Si＝f(S’i，u，Ti)(i＝1，2，···，m)，从而获得深层-超深层条件下目标层岩石力学参数的预测值。

Claims (5)

  1. 一种考虑温度效应的深层-超深层岩石力学参数预测方法，其特征在于步骤如下：
    步骤1，开展精细区域地质调查与地球物理勘探，查明目标层年代、埋藏深度和温度特征，并计算提取到地表目标层岩芯的升降温速率比；
    步骤2，采集多个未经历深-超深埋藏作用的目标层新鲜试样，采集数量由目标温度级别确定，记为A系列试样；采集经历过深层-超深层埋藏作用的同一目标层内不同深度的钻井岩芯样品，记为B系列试样；然后将所有样品加工成岩石力学实验试样，并测试每个试样的矿物成分及含量；
    步骤3，根据步骤2的实验测试结果，从A系列试样中优选矿物成分及含量与B系列试样最接近的试样，记为C系列试样，标号为C1，C2，···，Cn；
    步骤4，对步骤3获取的C系列中第1，2，···，m位偶数试样以速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，然后在相应的目标温度下分别开展岩石力学实验，获取不同目标温度条件下岩石力学参数S集，记为L1(x1，x2，···，xk)，L2(x1，x2，···，xk)，···，Lm(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；
    步骤5，对步骤3获取的C系列中第1，2，···，m位奇数试样以步骤4中同样非常慢的速率v1分别升温到目标温度T1，T2，···，Tm后恒温2h，然后C系列所有奇数试样再以非常快的速率v2降温到室温T0，最后在温度T0下开展岩石力学实验，获取不同目标温度条件下岩石力学参数S’集，记为L’1(x1，x2，···，xk)，L’2(x1，x2，···，xk)，···，L’m(x1，x2，···，xk)，其中，x1，x2，···，xk为不同的岩石力学参数；
    步骤6，基于步骤4和步骤5的结果，构建岩石力学参数S集与S’集、升降温速率比u＝v1/v2、目标温度T之间的量化关系：Si＝f(S’i，u，Ti)(i＝1，2，···，m)；从而获得Si与S’、i、u和Ti之间的函数关系；
    步骤7，对步骤2获取的B系列试样开展室温T0条件下的岩石力学实验，获取的岩石力学即为深层-超深层条件下目标层钻井岩芯的S’集；
    步骤8，结合步骤1获取目标的深层-超深层温度、升降温速率比以及步骤7中获取的深层-超深层条件下目标层钻井岩芯岩石力学参数集S’集代入步骤6中获取的函数关系式：Si＝f(S’i，u，Ti)(i＝1，2，···，m)，从而获得深层-超深层条件下目标层岩石力学参数的预测值。
  2. 按照权利要求1所述的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其特征在于：上述步骤1中优选的是，基于三维地震精细解释，确定目标层年代和埋藏深度情况；目标层温度特征由地层测试获取；升温速率为目标层温度与其年代之比；降温速率为目标层温度与提升至地表时间之比；升降温速率比为升温速率与降温速率的比值。
  3. 按照权利要求1所述的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其特征在于：上述步骤2中优选的是，A系列样品数量不少于20件，每件的尺寸应大于10cm×10cm×10cm；B样品为柱塞状样品，直径2.5cm，长度大于8cm；岩石力学实验试样为柱塞状，直径为2.5 cm，高为5cm；试样矿物成分及含量利用X-射线衍射实验获取；深层为埋深4500～6000m，超深层为埋深大于6000m。
  4. 按照权利要求1所述的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其特征在于：所述速率v1为0.01℃/min，速率v2为1℃/min。
  5. 按照权利要求1所述的一种考虑温度效应的深层-超深层岩石力学参数预测方法，其特征在于：上述步骤4和5中优选的是，目标温度T1，T2，···，Tm为40℃、60℃、80℃、100℃、120℃、140℃、160℃、180℃、200℃和220℃，室温T0为20℃。
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