基于反应动力学分布特征拟合和解释干酪根和页岩的多加热速率S2热解峰

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基于反应动力学分布特征拟合和解释干酪根和页岩的多加热速率S2热解峰

Advances in Geo-Energy Research, 2019, 3(1): 1-28

原文网址: http://www.astp-agr.com/index.php/Index/Index/detail?id=89   

       由三个或更多不同的加热梯度进行的热解试验产生的S2峰值数据中根据与活化能（E）和指前因子（A）提取反应动力学分布是一种成熟的技术。这些反应动力学分布对于确定经历一系列埋藏和热演化历史的页岩所生成的石油时间和成熟度至关重要。通常根据固定或常数A值配置的Arrhenius方程的导数来确定和定义反应动力学。尽管固定A值方法可以很好地拟合多速率热解数据，但本文显示涉及具有一系列E和A值的反应的Arrhenius方程公式同样适用于多速率热解数据。此外，具有可变E-A的动力学分布提供了更可靠的反应动力学，与几十年来已知的一系列干酪根类型所建立的反应动力学一致。优化器应用于首选的Arrhenius方程式来精确拟合以1°C为间隔，从250°C到700°C的多速率热解S2峰值数据，以获得反应增量和转化级数到一系列反应动力学（E-A对）。应用的方法包括两个步骤：步骤1找到最符合S2峰值温度的单个E-A对（多速率热解数据的三个或更多）；步骤2使用来自步骤1的E-A对作为其模态焦点，并使用11个不同反应的分布拟合完整的S2峰形。将该方法应用于10种已公布的干酪根和页岩的多速率热解数据的结果显示，可靠的动力学分布沿着已确定的干酪根和页岩的E-A趋势扩散。

Establishing credible reaction-kinetics distributions to fit and explain multi-heating rate S2 pyrolysis peaks of kerogens and shales

David A. Wood

(Published: 2018-09-01)

CorrespondingAuthor and Email: David A. Wood, dw@dwasolutions.com; ORCID: https://orcid.org/0000-0003-3202-4069

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Citation: Wood, D.A. Establishing credible reaction-kinetics distributions to fit and explain multi-heating rate S2 pyrolysis peaks of kerogens and shales. Advances in Geo-Energy Research, 2019, 3(1): 1-28, doi: 10.26804/ager.2019.01.01.

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ArticleType: Original article

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Abstract：

    Extracting reaction-kinetic distributions, in terms of activation energies (E) and pre-exponential factors (A), from the S2 peak data generated by pyrolysis tests conducted at three or more distinct heating ramps, is a well-established technique. These reaction-kinetics distributions are of paramount importance in establishing the timing and degree of petroleum generation from shales undergoing a range of burial and thermal histories. A commonly adopted approach is to determine and define reaction kinetics using a derivative of the Arrhenius equation configured in terms of a fixed/constant A value. Although the fixed-A approach can obtain good fits to multi-rate pyrolysis data, here it is shown that a formulation of the Arrhenius equation that involves reactions with a range of E and A values provides equally good fits to the multi-rate pyrolysis data. Moreover, the kinetic distributions with variable E-A provide more credible reaction kinetics consistent with those established for a range of kerogen types known for decades. To establish accurate fits to multi-rate pyrolysis S2 peak data at 1 ◦C intervals from 250 ◦C to 700 ◦C an optimizer is applied to the preferred Arrhenius equation formulation to derive reaction increments and transformation fractions to a range of reaction kinetics (E-A pairs). The methodology applied involves two steps: Step 1 finds the single E-A pair that best matches the S2 peak temperatures (three or more for multi-rate pyrolysis data); step 2 uses the E-A pair from step 1 as its modal focus and fits the full S2 peak shape using a distribution of 11 distinct reaction. This approach can replicate the fixed-A approach but is best applied using reactions with variable E-A values. The results of applying this method to multi-rate pyrolysis data for ten published kerogens and shales show credible kinetic distributions spread along the established E-A trend for kerogen/shales.

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Keywords: Kerogen-kinetics distributions, pyrolysis S2-peak shape analysis, mixing kerogen kinetics, multi-versus single-heating rate kinetics, case for varying A pre-exponential factor, applying optimizers to derive kinetic, distributions.