A study performed by Marbun et al. [1] claimed that “A new methodology to predict fracture pressure from former calculations, Matthew-Kelly and Eaton are proposed.” Also, Marbun et al.'s paper stated that “A new value of Poisson's and a stress ratio of the formation were generated and the accuracy of fracture gradient was improved.” We found those all statements are incorrect and some misleading concepts are revealed. An attempt to expose the method of fracture gradient determination from industry practice also appears to solidify that our arguments are acceptable to against improper Marbun et al.'s claims.

This paper is the first attempt to evaluate huff-n-puff air injection in a shale oil reservoir using a simulation approach. Recovery mechanisms and physical processes of huff-n-puff air injection in a shale oil reservoir are investigated through investigating production performance, thermal behavior, reservoir pressure and fluid saturation features. Air flooding is used as the basic case for a comparative study. The simulation study suggests that thermal drive is the main recovery mechanism for huff-n-puff air injection in the shale oil reservoir, but not for simple air flooding. The synergic recovery mechanism of air flooding in conventional light oil reservoirs can be replicated in shale oil reservoirs by using air huff-n-puff injection strategy. Reducing huff-n-puff time is better for performing the synergic recovery mechanism of air injection. O₂ diffusion plays an important role in huff-n-puff air injection in shale oil reservoirs. Pressure transmissibility as well as reservoir pressure maintenance ability in huff-n-puff air injection is more pronounced than the simple air flooding after primary depletion stage. No obvious gas override is exhibited in both air flooding and air huff-n-puff injection scenarios in shale reservoirs. Huff-n-puff air injection has great potential to develop shale oil reservoirs. The results from this work may stimulate further investigations.

Air injection is a good option to development light oil reservoir. As well-known that, reservoir heterogeneity has great effect for various EOR processes. This also applies to air injection. However, oil recovery mechanisms and physical processes for air injection in heterogeneous reservoir with dip angle are still not well understood. The reported setting of reservoir heterogeneous for physical model or simulation model of air injection only simply uses different-layer permeability of porous media. In practice, reservoir heterogeneity follows the principle of geostatistics. How much of contrast in permeability actually challenges the air injection in light oil reservoir? This should be investigated by using layered porous medial settings of the classical Dykstra-Parsons style. Unfortunately, there has been no work addressing this issue for air injection in light oil reservoir. In this paper, Reservoir heterogeneity is quantified based on the use of different reservoir permeability distribution according to classical Dykstra-Parsons coefficients method. The aim of this work is to investigate the effect of reservoir heterogeneity on physical process and production performance of air injection in light oil reservoir through numerical reservoir simulation approach. The basic model is calibrated based on previous study. Total eleven pseudo compounders are included in this model and ten complexity of reactions are proposed to achieve the reaction scheme. Results show that oil recovery factor is decreased with the increasing of reservoir heterogeneity both for air and N₂ injection from updip location, which is against the working behavior of air injection from updip location. Reservoir heterogeneity sometimes can act as positive effect to improve sweep efficiency as well as enhance production performance for air injection. High O₂ content air injection can benefit oil recovery factor, also lead to early O₂ breakthrough in heterogeneous reservoir. Well-type does not show great effect on production performance for air injection in extreme heterogeneous reservoir. While adopting horizontal producer is favourable to promote production performance for air injection in homogenous reservoir.

Thermal maturity indices and modelling based on Arrhenius-equation reaction kinetics have played an important role in oil and gas exploration and provided petroleum generation insight for many kerogen-rich source rocks. Debate continues concerning how best to integrate the Arrhenius equation and which activation energies (E) and frequency factors (A) values to apply. A case is made for the strong theoretical basis and practical advantages of the time-temperature index (∑TTI_ARR) method, first published in 1998, using a single, carefully selected E-A set (E = 218 kJ/mol (52.1 kcal/mol); A = 5.45E+26/my) from the well-established A-E trend for published kerogen kinetics. An updated correlation between ∑TTI_ARR and vitrinite reflectance (Ro) is provided in which the ∑TTI_ARR scale spans some 18 orders of magnitude. The method is readily calculated in spreadsheets and can be further enhanced by visual basic for application code to provide optimization. Optimization is useful for identifying possible geothermal gradients and erosion intervals covering multiple burial intervals that can match calculated thermal maturities with measured Ro data. A memetic optimizer with firefly and dynamic local search memes is described that flexibly conducts exploration and exploitation of the feasible, multi-dimensional, thermal history solution space to find high-performing solutions to complex burial and thermal histories. A complex deep burial history example, with several periods of uplift and erosion and fluctuating heat flow is used to demonstrate what can be achieved with the memetic optimizer. By carefully layering in constraints to the models specific insights to episodes in their thermal history can be exposed, leading to better characterization of the timing of petroleum generation. The objective function found to be most effective for this type of optimization is the mean square error (MSE) of multiple burial intervals for the difference between calculated and measure Ro. The sensitively-scaled ∑TTI_ARR methodology, coupled with the memetic optimizer, is well suited for rapidly conducting basin-wide thermal maturity modelling involving multiple pseudo-wells to provide thermal maturity analysis at fine degrees of granularity.

Oil recovery factor is one of the most important parameters in the development process of oil reservoir, especially in the low-permeability reservoir. In general, the determination of recovery factor can be obtained either experimentally or numerically. Experimental method is often time-consuming and expensive, while numerical method has been always confined to narrow range of application or relatively large error. Recently, an intelligent method has been proven as an efficient tool to model the complex and nonlinear phenomena. In this work, an intelligent model based on support vector machine in combination with the particle swarm optimization (PSO-SVM) technique was established to predict oil recovery factor in the low-permeability reservoir. Input variables of the proposed PSO-SVM model with the aid of a grey correlation analysis method are permeability, well spacing density, production-injection well ratio, porosity, effective thickness, crude oil viscosity and output parameter is oil recovery factor of low-permeability reservoir. The accuracy and reliability of the proposed model were evaluated through 34 data sets collected in the open literature and compared with PSO-BP neural network, empirical method from Oil and Gas Company. The results indicated that the PSO-SVM model gives the best results with average absolute relative deviation (AARD) of 3.79%, while AARDs for the PSO-BP neural network and empirical method are 9.18% and 10.0%, respectively. Furthermore, outlier detection was used on the basis of whole data sets to definite the valid domains of PSO-SVM and PSO-BP models by detecting the probable doubtful recovery factor data in the low-permeability reservoir.

Aiming at the actual demand of Guan 109-1 block in Dagang oilfield, by means of instrumental analysis, chemical analysis, modern physical simulation, viewing polymer viscosity and seepage characteristic as evaluation index, the experimental research on the influence of water disposal method on the property of chemical oil-displacement agent was carried out. Results showed that through adding scaling agent, scale was formed because of the reaction between scaling agent and Ca²⁺, Mg²⁺ in the flooding water, which could enhance the viscosity of polymer solution. Through comparing the resistance factor and residual resistance factor of polymer solution which was respectively prepared with flooding water, softened water and scale, the resistance factor and residual resistance factor of polymer solution with scale was the largest, that of polymer solution prepared with softened water was second and that of polymer solution prepared with flooding water came last. Furthermore, scaling agent weakened the gelling effect between cross-linking agent Cr³⁺ and polymer molecule chains. The earlier the cross-linking agent Cr³⁺ was added, the larger the polymer viscosity, resistance factor and residual resistance factor of Cr³⁺ polymer were.

Adsorptive component of produced water (PW) coagulation using Tympanotonos Fuscatus coagulant (TFC) was studied. Influence of the following parameters: pH, coagulant dose, settling time, and temperature were investigated. The functional group, crystalline nature, morphological observation and thermal characteristics of the sample were evaluated. Equilibrium data were analyzed using Langmuir, Freundlich, Temkin, Frumkin, and Dubinin-Radushkevich (D-R) adsorption isotherms. The kinetics data were fitted to reversible first order, pseudo-first-order, pseudo-second-order, elovich, intra-particle diffusion and Boyd kinetic models. Adsorption Gibbs energy, enthalpy and entropy were evaluated. Equilibrium data best fitted the Langmuir isotherm (R² > 0.99; X² < 1.6; SSE < 1.6). Reversible first order model correlated best to the kinetics data. The values of process average Gibb's free energy, enthalpy and entropy were 30.35, 27.88 and 0.1891 kJ/mol, respectively. The process was spontaneous, feasible and endothermic in nature. The maximum efficiency of 83.1% was favored at pH 2.0. This study indicated significant adsorptive component, while using Tympanotonos Fuscatus extract as readily available, renewable, ecofriendly bio -coagulant for efficient treatments of PW.

Thermal fracturing could occur during cold CO₂ injection into subsurface warm rock formations. It can be seen in a variety of fields such as carbon geo-sequestration, unconventional gas development, enhanced oil recovery, geothermal energy extraction, and energy geological storage systems. In CO₂ geosequestion, limited degree of thermal fracturing due to the cooling effects of cold CO₂ injection will enhance well injectivity, especially for those storage formations of low permeability. Thermal fracturing can therefore potentially enhance the injection efficiency and make positive impact on commercialization of CO₂ geological storage. However, excessively developed fractures could break down the caprock and cause potential CO₂ leakage into overlying rock formations. Risk analysis has to be done based on thermal fracturing simulation in order to maintain caprock integrity.

Simulation of thermal fracturing during cold CO₂ injection involves the coupled processes of heat transfer, mass transport, rock deforming as well as fracture propagation. To model such a complex coupled system, a fully coupled finite element framework for thermal fracturing simulation is presented. This framework is based on the theory of non-isothermal multiphase flow in fracturing porous media. It takes advantage of recent advances in stabilized finite element and extended finite element methods. The stabilized finite element method overcomes the numerical instability encountered when the traditional finite element method is used to solve the convection dominated heat transfer equation, while the extended finite element method overcomes the limitation with traditional finite element method that a model has to be remeshed when a fracture is initiated or propagating and fracturing paths have to be aligned with element boundaries.

Artificial intelligence (AI) methods and applications have recently gained a great deal of attention in many areas, including fields of mathematics, neuroscience, economics, engineering, linguistics, gaming, and many others. This is due to the surge of innovative and sophisticated AI techniques applications to highly complex problems as well as the powerful new developments in high speed computing. Various applications of AI in everyday life include machine learning, pattern recognition, robotics, data processing and analysis, etc. The oil and gas industry is not behind either, in fact, AI techniques have recently been applied to estimate PVT properties, optimize production, predict recoverable hydrocarbons, optimize well placement using pattern recognition, optimize hydraulic fracture design, and to aid in reservoir characterization efforts. In this study, three different AI models are trained and used to forecast hydrocarbon production from hydraulically fractured wells. Two vastly used artificial intelligence methods, namely the Least Square support Vector Machine (LSSVM) and the Artificial Neural Networks (ANN), are compared to a traditional curve fitting method known as Response Surface Model (RSM) using second order polynomial equations to determine production from shales. The objective of this work is to further explore the potential of AI in the oil and gas industry. Eight parameters are considered as input factors to build the model: reservoir permeability, initial dissolved gas-oil ratio, rock compressibility, gas relative permeability, slope of gas oil ratio, initial reservoir pressure, flowing bottom hole pressure, and hydraulic fracture spacing. The range of values used for these parameters resemble real field scenarios from prolific shale plays such as the Eagle Ford, Bakken, and the Niobrara in the United States. Production data consists of oil recovery factor and produced gas-oil ratio (GOR) generated from a generic hydraulically fractured reservoir model using a commercial simulator. The Box-Behnken experiment design was used to minimize the number of simulations for this study. Five time-based models (for production periods of 90 days, 1 year, 5 years, 10 years, and 15 years) and one rate-based model (when oil rate drops to 5 bbl/day/fracture) were considered. Particle Swarm Optimization (PSO) routine is used in all three surrogate models to obtain the associated model parameters. Models were trained using 80% of all data generated through simulation while 20% was used for testing of the models. All models were evaluated by measuring the goodness of fit through the coefficient of determination (R²) and the Normalized Root Mean Square Error (NRMSE). Results show that RSM and LSSVM have very accurate oil recovery forecasting capabilities while LSSVM shows the best performance for complex GOR behavior. Furthermore, all surrogate models are shown to serve as reliable proxy reservoir models useful for fast fluid recovery forecasts and sensitivity analyses.

In this work, the performance of CO₂ absorption into aqueous 2-amino-2-methyl-propanol (AMP) solution was investigated by measuring the amount of CO₂ in the liquid phase during CO₂ absorption process to identify initial CO₂ absorption rate. Then, the porous media material named as MCM41 was introduced into the amine solution to test its influence on CO₂ absorption. It was found that MCM41 increased initial CO₂ absorption rate and enhanced CO₂ absorption process. The physico-chemical properties of MCM41 were characterized in terms of specific surface area, average pore diameter, total pore volume and chemical properties, the amount of acidic sites and the Brϕnsted/Lewis (B/L) acid sites ratio. Results showed that MCM41 was a type of Lewis acid catalyst with large specific surface area and pore volume. In addition, the pKa of AMP solution with and without MCM41 was obtained using acid titration technology to help understand the effect brought by MCM41. A mechanism illustrating how MCM41 increases the CO₂ absorption rate of the AMP solution was proposed and demonstrated that MCM41 is a potential material for enhancing CO₂ absorption.

Depleted gas reservoirs are recognized as the most promising candidate for carbon dioxide storage. Primary gas production followed by injection of carbon dioxide after depletion is the strategy adopted for secondary gas recovery and storage practices. This strategy, however, depends on the injection strategy, reservoir characteristics and operational parameters. There have been many studies to-date discussing critical factors influencing the storage performance in depleted gas reservoirs while little attention was given to the effect of residual gas. In this paper, an attempt was made to highlight the importance of residual gas on the capacity, injectivity, reservoir pressurization, and trapping mechanisms of storage sites through the use of numerical simulation. The results obtained indicated that the storage performance is proportionally linked to the amount of residual gas in the medium and reservoirs with low residual fluids are a better choice for storage purposes. Therefore, it would be wise to perform the secondary recovery before storage in order to have the least amount of residual gas in the medium. Although the results of this study are useful to screen depleted gas reservoirs for the storage purpose, more studies are required to confirm the finding presented in this paper.

Through the single row drilling experiment, this paper studied the regularity of the tooth shape parameter's influence to the disc teeth's rock-breaking effect, which provided some basis for the composite teeth type roller bit's combined experimental study and the structure design of the tooth type. This experimental research is only for the circular arc disc teeth which is arranged on the composite teeth type roller bit's main tooth. The experiments were designed using the method of orthogonal design and the results were analyzed by the fuzzy optimization method. The results show that the disc tooth's drilling effect is the best when the tip diameter is 2 mm, taper angle is 30° and the groove number is 8, and the disc tooth's drilling effect is the second best when the tip diameter is 3 mm, taper angle is 30° and the groove number is 7. The above two combined ways of drilling effect's difference is very small (the difference of the degree of the membership is 0.003).