Journal of Natural Gas Science and Engineering最新文献

In the petroleum industry, enhanced oil recovery (EOR) techniques employ foam extensively to establish conformance control in heterogeneous and fractured reservoirs in order to increase the sweep efficiency. In such applications, foam performance evaluation under complex subsurface conditions is pivotal for the effective and optimized deployment of foam treatment. However, there is a scarcity of hydrocarbon gas foam generation and evaluation studies that examine the relationships between foam performance and the critical foam parameters at high-pressure and high-temperature conditions.

This study aims at methodically investigating the effects of several foam parameters on methane foam performance in water-wet proppant packs under harsh operating conditions. This is in relation to the technical needs of hydrocarbon foam injection into hydraulically-induced, propped fractures in unconventional oil reservoirs. To this end, a state-of-the-art experimental foam generation apparatus was designed, fabricated, and commissioned. We performed a large number of foam flow experiments on proppant packs using methane gas and different foaming agents at 3500 psi and 115 °C. Anionic and amphoteric surfactants were employed to probe the effect of their ionic nature on foam performance. Foam performance sensitivities to various foam generation parameters and operating conditions, such as surfactant concentration, gas fraction, total injection rate, operating pressure, salinity, and proppant pack length were investigated. To this end, steady-state pressure drops across the proppant packs during foam generation and foam's apparent viscosity were measured to quantify the foam performance of surfactants. The results were then analyzed to determine optimum values of the foam parameters and the interplay between these parameters are discussed here. The systematic results achieved from this work are in agreement with the trends available in the literature and provide new insights into complexities of in situ foam generation in water-wet, unconsolidated porous media at extreme reservoir conditions.

In this study, an in situ synchrotron radiation small-angle X-ray scattering (SAXS) experiment is used to characterize the evolution of coal nanopore structures under uniaxial compression. The variation in the coal nanopores is measured by analyzing the obtained scattering data. From the results, the coal scattering data show a positive Porod deviation in which the deviation slope decreases with increasing stress. Smaller nanopores are more sensitive to uniaxial compressive stress. There is a positive correlation between scattering intensity I and stress at less than 30 nm. The scattering intensity I of pores larger than 30 nm is negatively correlated with uniaxial compressive stress. The structure of smaller pores is more complex. The surface fractal dimension D_S and pore fractal dimension D_P increases and decreases with increasing uniaxial compressive stress, respectively. The specific surface area is positively correlated with D_S. In the measuring range of 3–80 nm, the coal nanopores show a bimodal distribution. At the stage of below 0.6σ_p, the average diameter decreases by 1.98%, the porosity and specific surface area increases by 6.21% and 31.5%, respectively; At the stage of above 0.6σ_p, the average diameter decreases by 1.04%, the porosity and specific surface area increases by 1.18% and 5.57%, respectively. These results suggest that the variation of coal nanopores with stress have phased characteristics, and the evolution of the coal nanopores under uniaxial stress can be divided into two stages. In the nanopore fracture stage, the nanopores are deform, fracture and create new smaller pores with increasing stress, and the roughness of pore surface increase. In the nanopore closure stage, high stress intensifies the degree of pore fracture, and nanopores begin to close and disappear. This study reveals the evolution characteristics of the pore structures of coal under uniaxial compression at the nanoscale.

Capillary trapping is a prominent short-term trapping mechanism that achieves the maximum storage capacity and ensures the integrity of CO₂ sequestration in deep saline aquifers on an industrial scale. To maximize capillary trapping, fluid injection scenarios need to be investigated, and the fluid flowing characteristics in porous reservoir media need to be acknowledged. In this study, magnetic resonance imaging (MRI) technology was used to examine the distribution of three fluid pairs in fractured carbonate rock and sandstone under reservoir conditions, and the relative permeability and capillary pressure were determined based on their capillary end saturation profiles. The initial gas saturation increased with the injection rate, and the fractured structure created a preferential flow channel that affected the saturation distribution. Differences in interfacial tension and wettability lead to different capillary pressures. The low interfacial tension of the scCO₂/water fluid pair and its strong water-wet properties in sandstone caused high relative permeability and residual gas saturation. These results imply that the influence of the fluid injection method and reservoir properties on capillary trapping characteristics should be investigated in detail before implementing CO₂ geological sequestration.

Natural gas hydrates have attracted many attentions recently as a promising energy, the exploitation of which will cause complicated multifield coupled behavior of hydrate-bearing sediments. As sediments usually vary from tens to hundreds of meters, the gravity effect on gas-liquid migration and soil deformation may not be completely ignored. This paper develops a new thermo-hydro-chemo-mechanical model to investigate the sediment behavior during the hydrate dissociation. The equations of gas-liquid migration are numerical solved with explicit incorporation of hydrate dissociation process. The numerical stability and efficiency have been improved by expanding the Taylor series of the source terms and making the first-order approximation. Furtherly, pre-calculation procedures have been considered to obtain the initial state of field variables. Pilot-scale model results show that the gas-liquid migration, soil deformation and NGH dissociation are accelerated when the gravity effect is present. During the exploitation, a dissociation front can be observed, and gas-liquid migration and hydrate dissociation dominate the process alternatively, leading to first decrease and subsequent increase of gas saturation and continuous rise of liquid saturation. Moreover, it is inferred that marginal enhancement of gas production can be achieved with the increase of wellbore lengths, but it should not exceed 75% of the reservoir thickness.

A clear understanding of the replacement characteristics and kinetic mechanism of CO₂–CH₄ hydrate has great significance for natural gas hydrate (NGH) exploitation. This paper presents a comprehensive overview on the research progress of kinetics on CH₄ recovery from NGH by CO₂ replacement, especially with CO₂-containing mixed gas. The promoting effect of small molecule gas such as H₂ and N₂ on the replacement process of CO₂–CH₄ hydrate and its internal mechanism are deeply analyzed. Furthermore, based on the current conclusions obtained, the existing problems and future development directions of the CH₄ recovery from NGH by CO₂-containing gas mixture are pointed out.

Increasing attention has been paid to the site selection of Underground Gas Storage (UGS) due to the growing demand for natural gas peak shaving. Existing studies have made a practical contribution to this field based on the multidimensional geological exploration data and the multi-criteria decision-making method. However, previous studies mainly focused on screening or ranking technologies with different principles, which means only the attributes of UGS in the design period were considered while the performance in the operation period was ignored. The operation plan and economic performance are considerable concerns to the UGS investors especially when this type of storage facility was unbundling from other sectors in natural gas companies. To solve the UGS site selection problems more comprehensively and practically, the geological conditions and the injection & extraction plan in the operation period are considered Simultaneously. A case from the S-X area in China indicates that: 1. The improved multi-period optimization model of the natural gas (NG) supply chain can obtain the injection and production plan of UGS which are the basic parameters for the economic analysis. 2. The top potential UGS estimated by geological conditions may take inferior performance in the operation stage (less peak shaving amount, low economic profits, and high freight of NG supply chain), so the UGS investors should consider the potential profits when the finished UGS is put into operation. The proposed framework can be a new theoretical guideline for the site selection problems of UGSs and can help UGS investors judge their investment.

In the past several decades, machine learning has gained increasing interest in the oil and gas industry. This paper presents a comprehensive review of machine learning studies for drilling applications in the following categories: (1) drilling fluids; (2) drilling hydraulics; (3) drilling dynamics; (4) drilling problems; and (5) miscellaneous drilling applications. In each study, the machine learning algorithm(s), sample size, inputs and output(s), and performance are extracted. In addition, similarities of studies in each category are summarized and recommendations are made for future development.

The gas extraction environment in coal seam exhibits uniaxial strain condition with constant overlying strata stress and horizontal strain. Simulating this environment in laboratory often ignores true triaxial stress state, so the difference in horizontal stresses reduction and the accompanying permeability evolution remain ambiguous. Therefore, this study conducted the true triaxial stress and permeability response tests simulating gas extraction environment under shallow and deep in-situ stress conditions. To quantify gas adsorption effect, the adsorbed (CO₂) and non-adsorbed (He) gases were also used. The results indicated that the intermediate and minimum principal stresses, i.e., σ₂ and σ₃, exhibited a linear decreasing trend during gas depletion, but showed more decreases in stress when the intermediate and minimum principal strains, i.e., ε₂ and ε₃, recover under high gas pressure depletion. High true triaxial stress enhanced the compressibility of pores and fractures in coal, resulting in low horizontal deformation and stress reduction gradient during gas depletion. Similarly, the reduction gradient of σ₂, m_σ2, was less than that of σ₃. This suggested that the difference between horizontal stresses also increased during coalbed methane (CBM) extraction, which exacerbated the risk of coal body damage. For different gas depletion, the stress reduction gradient exhibited m_He < 1 and m_CO2 > 1, which was related to the relative affinity of different gas species for the adsorption medium. A significant matrix shrinkage effect resulted in a more pronounced stress reduction. For permeability, the permeability increased exponentially during CO₂ depletion, while the permeability of helium exhibited a decreasing followed by an increase with decreasing gas pressure. This is related to the competing mechanism and synergistic effect of the adsorptive gas desorption, effective stress effect, and slippage effect. We quantified the contribution and mechanism of the three to the permeability separately. The permeability anisotropy ratio (A_r) decreased exponentially during gas depletion.

Matrix shrinkage is a factor that must be considered in the dynamic permeability model of coal reservoirs. The mechanism of matrix shrinkage affecting confining pressure (confining pressure mechanism) has been modeled by analogy with thermal expansion, and it is widely used in permeability model construction. However, the mechanism of matrix shrinkage affecting porosity (porosity mechanism) has not been widely recognized and modeled, and this mechanism independently controls porosity even though neither confining pressure nor pore pressure changes (only the replacement of different adsorbed gases occurs). The porosity mechanism and a permeability model that takes into account the dual mechanism have been modeled recently. This study compares the two mechanisms of matrix shrinkage by theoretical analysis of the mathematic relations in the permeability models considering different mechanisms and by finite element numerical simulations of coalbed methane development considering different mechanisms. Theoretical analysis shows that the effect of the porosity mechanism on permeability is more than 1.5 times that of the confining pressure mechanism. the numerical simulations results show that: considering the porosity mechanism and the confining pressure mechanism simultaneously allows for a larger and earlier improvement in permeability and a larger reservoir area to improve, and a significant improvement of 28% in gas production rate occurs compared with the case only the confining pressure mechanism were considered. This study reveals the importance of porosity mechanism in describing the dynamic evolution of reservoir permeability and production dynamics accurately, and provides a scientific basis for coalbed methane development.

There are many applications with the two-phase flow of gas (hydrocarbon, non-hydrocarbon, and their mixture) and water in different courses of gas recovery from natural gas resources and gas storage/sequestration programs. As the interface of gas-water is crucial in such systems, precise prediction of gas-water interfacial tension (IFT) can aid in the simulation and development of such processes. Artificial intelligence techniques (AIT) are being used to estimate IFT. In this paper, the IFT of the gas and water system was estimated based on models built using a comprehensive data set comprised of 2658 experimental data points. These cover a wide range of input parameters, i.e., specific gravity (0.5539–1.5225), temperature (278.1–477.5944 K), pressure (0.01–280 MPa), and water salinity (0–200,000 ppm). The intelligent models include Least-Squares Boosting (LS-Boost), Multilayer perceptron (MLP), Least Square Support Vector Machine (LSSVM), and Committee machine intelligent system (CMIS). The models reproduce the IFT data in 7.4–81.69 mN/m. The modeling approaches contain new hybrid forms in which Imperialist Competitive Algorithm (ICA), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Levenberg-Marquardt algorithm (LM), Bayesian regularization algorithm (BR), Scaled conjugate gradient algorithm (SCG), and Coupled Simulated Annealing (CSA) were used for optimization and learning purposes. Statistical and graphical analyses were implemented to check the agreement between the prediction and evaluation data. The results show a reasonable coherence for most models, among which the CMIS approach exhibited a promising performance. CMIS was accurate even in conditions of varying specific gravity, pressure, temperature, and salinity. The findings were also compared with available models in the literature and demonstrated superior predictions of the CMIS model. Also, outlier detection by the Leverage approach demonstrates the validity of the gathered dataset and, subsequently, the CMIS model.