A Prediction Model for Methane Adsorption capacity in Shale Gas Reservoirs
Estimation of methane adsorption capacity is crucial for the characterization of shale gas reservoirs. The methane adsorption capacity in shales is measured using high-pressure methane adsorption to obtain the adsorption isotherms, which can be fitted by Langmuir model. The determined Langmuir parameters can provide the methane adsorption capacity under actual reservoir conditions. In this study, a prediction model for the methane adsorption in shales was constructed based on 66 samples from 6 basins in China and Western Australia.
Jie Zou and Reza Rezaee
Curtin WA School of Mines: Minerals, Energy and Chemical Engineering, Perth 6151, Australia
Received: 5 December 2018 / Accepted: 13 January 2019 / Published: 16 January 2019
The model was established in four steps: a model of Langmuir volume at experimental temperature, the temperature dependence of Langmuir volume, a model of Langmuir pressure, the temperature dependence of Langmuir pressure. In the model of Langmuir volume at experimental temperature, total organic carbon (TOC) and clay content (Vsh) were considered. A positive relationship was observed between the TOC and the temperature effect on the Langmuir volume.
As the Langmuir pressure is sensitive to various factors, the Langmuir pressure at experimental temperature shows no trend with the TOC, clay content and thermal maturity, but a positive trend with the Langmuir volume. The results of this study can help log analysts to quantify adsorbed gas from well-log data since TOC and Vsh, which are the measure inputs of the introduced models, can be obtained from well-log data as well.
Shale gas contains not only free gas in pore volume but also a significant amount of adsorbed gas on the surface area of the pore wall . The usual method for assessing the methane adsorption capacity in shale gas is high-pressure methane adsorption experiment to obtain adsorption isotherms. The high-pressure methane adsorption isotherms can be fitted by many models. The most popular model is the Langmuir model because of its simplicity and accuracy [2,3]. Langmuir parameters such as Langmuir volume and Langmuir pressure can be determined using Equation (1) to characterize the methane adsorption isotherms of shale samples .
where VL is the Langmuir volume, defined as the maximum gas content that can be adsorbed on shale at an infinite pressure; PL is the Langmuir pressure, defined as the pressure at which one-half of the Langmuir volume can be adsorbed; Vads is the adsorbed gas content and P is the experimental pressure.
With the Langmuir parameters, the methane adsorption capacity of shale sample at certain pressure can be predicted. Thus, it is necessary to have a quantitative model of the Langmuir parameters for evaluating the methane adsorption capacity in shales.
However, the Langmuir parameters are controlled by various factors . It has been reported that the Langmuir volume is related to the compositional properties (total organic content, thermal maturity, and clay minerals content), pore structure properties (specific surface area and micropore volume) and reservoir conditions (pressure, temperature and moisture content) [6,7,8,9]. As for the Langmuir pressure, the most considered controlling factor is temperature, but it was also observed that the Langmuir pressure is related to composition and volume of small pores [6,10,11].
Furthermore, a power-law decrease trend was found between the Langmuir pressure and Vitrinite Reflectance . Based on the controlling factors of the Langmuir parameters, the prediction model for the methane adsorption capacity in shale gas has been constructed by many scholars [11,12,13].
As listed in Table 1, however, the considered factors in the models are different: in terms of the Langmuir volume, TOC is the only considered factor for organic-rich shales by Zhang, Ellis ; apart from the TOC, Liu, Chen  also considered the clay content for low TOC shales. Li, Tian  used other parameters in the model to improve accuracy, such as the amount of residual hydrocarbon and temperature.
For the Langmuir pressure, Zhang, Ellis  classified the shale samples by the thermal maturity and employed the temperature to model the Langmuir pressure; the temperature is the only considered factor in the model of the Langmuir pressure by Liu, Chen , while the content of clay minerals, illite, feldspar, and carbonate was used by Li, Tian . However, some of the considered parameters are hard to obtain from well log, such as the content of residual hydrocarbon, illite, feldspar, and carbonate. Furthermore, the prediction models of methane adsorption capacity in previous studies were established on data from specific formations or basins. To assess the methane adsorption capacity in shales, it is required to establish a prediction model based on representative data and proper factors.
Table 1. Considered factors of the prediction model for Langmuir parameters in previous studies.
In this study, we analyzed the experiment results of high-pressure methane adsorption on shales using available published and our unpublished data. The experimental procedures of our unpublished data have been described in a previous work . Given that the experimental temperatures are not constant among the related studies, the Langmuir parameters were modeled at experimental temperature first and then the temperature dependence of Langmuir parameters was explored. With various shale samples, the results can contribute to the evaluation of the methane adsorption in shales.
As the high-pressure methane adsorption experiments are intrinsically controlled by various factors , all the considered data must be obtained under similar experimental conditions (e.g., dry with the particle size of <250 µm) with available compositional and geochemical information. It is worth mentioning that data of wet shale samples were not employed because the moisturization level is not constant and the number of shale samples in wet condition is constrained. Meanwhile, the 60 mesh (<250 µm) was applied in this study, as it has been widely used in the related studies.
In addition, 60-80 mesh was also carried out with close particle diameter to 60 mesh to involve as much data as possible. Under these conditions, a total of 66 samples from 6 Basins in China and Western Australia were studied [14,16,17,18,19]. The samples have a TOC range of 0.23 to 28.48 wt % and clay content range of 20.1 to 83.5. Thermal maturity of the samples directed measured by rock-eval in Tmax, ranges from 424 to 589 °C. Vitrinite Reflectance (Ro) is not used for the thermal maturity, because the convention from Tmax to Ro is not constant for different basins. The wide ranges of compositional and geochemical parameters indicate good representativeness of the studied shale samples. The detailed information about the studied samples is provided in an Appendix at the end of the paper.
Results and Discussion
Since the studied shale samples were measured at different temperatures and the amount of data at each high temperature is limited, a model of the Langmuir volume at experimental temperature (30 °C) was considered first. The experimental temperature in the range of 25–30 °C was regarded as the similar condition due to the little temperature difference. Secondly, the model was updated for the methane adsorption under actual reservoir conditions, at higher reservoir temperature.
Model of Langmuir Volume at Experimental Temperature
As the collected adsorption data of 10 samples are not available at experimental temperature, a total of 56 samples in 5 basins were studied for the model of Langmuir volume at experimental temperature. Figure 1 shows the positive relationship between the TOC and Langmuir volume at experimental temperature, with a coefficient of determination of 0.87, indicating the critical role of organic matter in methane adsorption in shales. However, more data is still required as the shale samples in the TOC range of 10 to 25 wt % is limited in Figure 1.
Figure 1. The relationship between the TOC and Langmuir volume at experimental temperature (30 °C) for the studied shale samples.
Comparing with the TOC, clay content appears to have a much less relationship with the Langmuir volume (Figure 2), demonstrating a limited contribution to the methane adsorption. However, it has been reported that the contribution of clay minerals to the methane adsorption is significant for low TOC shale samples [6,20]. To explore the effect of clay on methane adsorption in shales, the studied samples were classified into three groups of low (0–1.5%), medium (1.5–3%), and high (>3%) based on the TOC content.
Figure 2. A weak relationship exists between the clay content and Langmuir volume at experimental temperature (30 °C) for the studied shale samples.
As for the clay content, Figure 3 displays a good relationship between the clay content and Langmuir volume at experimental temperature for the low TOC samples but not for medium and high TOC samples. The phenomenon demonstrates that the clay content is the critical controlling factor of methane adsorption for low TOC shales, but its effect weakens in higher TOC samples due to the organic matter. This is because both organic matter and clay minerals can adsorb methane.
Comparing with low TOC samples, high TOC samples have smaller proportion of methane adsorbed on clay content. Furthermore, the slopes of the relationship between the clay content and Langmuir volume at experimental temperature for the three groups of shales have no big difference, with the range of 1 to 1.73. The similarity of the slopes indicates that there is no remarkable difference between organic-poor and organic-rich shales with respect to the adsorption capacity of clay minerals. Note that the type of clay minerals was not specified for their relationship to Langmuir volume. The reason is that the content of each clay type is hard to obtain directly from well log and illite dominates the clay content for the applied data.
Figure 3. The relationship between the clay content and Langmuir volume at experimental temperature for low, medium and high TOC shale samples.
Apart from the TOC and clay content, thermal maturity is also believed to control the methane adsorption in shales. It has been reported that the relationship between the TOC-normalized maximum methane adsorption capacity (Langmuir volume divided by the TOC) and thermal maturity is positive for mature shales and negative for over mature shales [5,11]. However, the thermal maturity in the form of Tmax displays no relationship to the TOC-normalized Langmuir volume at experimental temperature for the collected data (Figure 4).
The phenomenon can be explained in two aspects: 1. The TOC-normalized Langmuir volume can be influenced by clay content especially for the low TOC shale; 2. other factors such as kerogen type, thermal maturity levels, and depositional environment may have impacts on methane adsorption capacity. Therefore, the thermal maturity is not considered in the model of the Langmuir volume at experimental temperature.
Figure 4. There is no meaningful relationship between the TOC-normalized Langmuir volume at experimental temperature and Tmax for the studied shale samples.
According to the linear relationship of the Langmuir volume to TOC and clay content, a model for the Langmuir volume at experimental temperature is proposed in the form of the following equation:
where a, b and c are the fitting coefficients, which can be determined using the 56 studied samples in by multiple linear regression. Thus, the prediction model is written as follows:
where VL is the Langmuir volume at experimental temperature, scf/ton; TOC is the total organic carbon, wt %; Vsh is the total clay content, %.
The predicted Langmuir volume and measured Langmuir volume at experimental temperature are plotted in Figure 5, with R-square 0.88.
Figure 5. The relationship between the measured and predicted Langmuir volume at experimental temperature.