Petroleum最新文献

Natural gas is easily soluble in oil-based muds (OBM), leading to complex flow behavior in wellbores, especially in horizontal wells. In this study, a new transient flow model considering wellbore-formation coupling and gas solubility on flow behavior is developed to simulate gas kicks during horizontal drilling with OBM. Furthermore, the effect of gas solubility on parameters such as bottom-hole pressure (BHP), gas void fraction and mixture velocity in the flow behavior is analyzed. Finally, several critical factors affecting flow behavior are investigated and compared to gas kicks in water-based muds (WBM) where the effect of solubility is neglected. The results show that the invading gas exists as dissolved gas in the OBM and as free gas in the WBM. Before the gas escapes from the OBM, the pit gain is zero and there is barely any change in the BHP, annulus return flow rate and mixture velocity, which means that detecting gas kicks through these warning signs can be challenging until they get very close to the surface and develop rapidly. However, in WBM drilling, these parameters change quickly with the increasing gas kick time. Additionally, for both cases, the longer the horizontal length and the greater reservoir permeability, the greater the decrease in BHP, and the shorter the time for gas to migrate from the bottom-hole to the wellhead. A larger flow rate contributes to a greater initial BHP and a lesser BHP reduction. This research is of value in characterizing gas kick behavior and identifying novel ways for early gas kick detection during horizontal drilling with OBM.

This paper comprehensively reviews the application and research progress of CO₂ fracturing fluids in China, highlights the existing issues and puts forward suggestions for future development. Three types of fracturing fluid systems containing CO₂, namely, CO₂ dry fracturing fluid, CO₂ energized fracturing fluid, and CO₂ foam fracturing fluid, are categorized based on the mass ratio and process difference between CO₂, water, and treatment agents. Field applications in China reveal several problem to be resolved: (1) The application scope of CO₂ fracturing fluids is restricted to depleted reservoirs, re-fracturing of old wells, and medium-deep reservoirs with low formation pressure coefficients; (2) different types of CO₂ fracturing fluids require different processes and ground supporting equipment; (3) optimization of CO₂ compatibility, functionality, temperature and salt tolerance, as well as the cost of treatment agents is necessitated; (4) existing CO₂ fracturing fluid system fail to perform well with low friction, low filtration, and high sand-carrying capacity. (5) there lacks a targeted industry standard for evaluation of performance of CO₂ fracturing fluid system and treatment agents. Therefore, in order to meet the goals of CCUS-EOR, CCUS-EGR, or integration of fracturing, displacement and burial by CO₂, efforts should be made in the aspects that followed, including in-depth investigation of the mechanism of CO₂ fracturing fluids, the adaptability and compatibility between existing equipment, different CO₂ fracturing fluid systems and processes, and construction of treatment agents, low-density proppants and high-performance systems of recyclability and industrial-grade. In addition, optimization of CO₂ fracturing fluid system based fracturing design is also crucial taking such related factors such as overall reservoir geological conditions, petrophysical properties, CO₂ transportation, and well site layout into consideration.

Miscible natural gas injection is widely considered as a practical and efficient enhanced oil recovery technique. However, the main challenge in this process is the high minimum miscibility pressure (MMP) between natural gas and crude oil, which limits its application and recovery factor, especially in high-temperature reservoirs. Therefore, we present a novel investigation to quantify the effect of chemical-assisted MMP reduction on the oil recovery factor. Firstly, we measured the interfacial tension (IFT) of the methane-oil system in the presence of chemical or CO₂ to calculate the MMP reduction at a constant temperature (373K) using the vanishing interfacial tension (VIT) method. Afterwards, we performed three coreflooding experiments to quantify the effect of MMP reduction on the oil recovery factor under different injection scenarios.

The interfacial tension measurements show that adding a small fraction (1.5 wt%) of the tested surfactant (SOLOTERRA ME-6) achieved 9% of MMP reduction, while adding 20 wt% of CO₂ to the methane yields 13% of MMP reduction. Then, the coreflooding results highlight the significance of achieving miscibility during gas injection, as the ultimate recovery factor increased from 65.5% under immiscible conditions to 77.2% using chemical-assisted methane, and to 79% using gas mixture after achieving near miscible condition. The results demonstrate the promising potential of the MMP reduction to significantly increase the oil recovery factor during gas injection. Furthermore, these results will likely expand the application envelop of the miscible gas injection, in addition to the environmental benefits of utilizing the produced gas by re-injection/recycling instead of flaring which contributes to reducing the greenhouse gas emissions.

Hydraulic fracturing is a mainstream technology for unconventional oil and gas reservoirs development all over the world. How to use this technology to achieve high-level oil and gas resource extraction and how to form complex fracture networks as hydrocarbon transportation channels in tight reservoirs, which depends to a large extent on the interaction between hydraulic and pre-existing cracks. For hydraulic fracturing of fractured reservoirs, the impact of natural fractures, perforation direction, stress disturbances, faults and other influencing factors will produce a mixed Ⅰ&Ⅱ mode hydraulic fracture. To forecast whether hydraulic fractures cross pre-existing fractures, according to elastic mechanics and fracture mechanics, a stress state of cracks under the combination of tensile (Ⅰ) and shear (Ⅱ) is presented. A simple mixed-mode Ⅰ&Ⅱ hydraulic fracture's crossing judgment criterion is established, and the propagation of hydraulic fractures after encountering natural fractures is analyzed. The results show that for a given approaching angle there exists a certain range of stress ratio when crossing occurs. Under high approaching angle and large stress ratio, it is likely that hydraulic cracks will go directly through pre-existing cracks. The reinitiated angle is always controlled within the range of approximately 30° among the main direction of penetration.

The ionic liquid, as a new treatment agent, has been increasingly applied in oil fields due to its strong temperature resistance, good solubility and high surface activity. In this paper, we systematically discuss the action mechanism and application effect of ionic liquids in oilfield chemistry. Ionic liquids can inhibit shale hydration expansion and reduce fluid loss through adsorption and intercalation, inhibit the formation of natural gas hydrate through imidazole five-membered ring structure as a space barrier, reduce viscosity of heavy oil by breaking chemical bonds of heavy oil macromolecules and charge transfer, improve oil displacement efficiency by forming ions pairs with carboxyl groups in crude oil, demulsify by forming channels between dispersed water droplets, acidify the formation by reacting with water to produce acid, interacts with organic material through weak hydrogen bonds and extracts it from oilfield wastewater, desulphurize by inserting sulfide molecules into the “stack” structure and form liquid inclusion complex, inhibit corrosion by forming a protective film on the metal surface. Based on the above aspects, the development direction of ionic liquids is proposed. The application of ionic liquids in oilfield chemistry is still in its infancy. It is urgent to fully explore the application performance of ionic liquids in oilfield chemistry, which also provides theoretical and technical supports for efficient reservoir development.

The technique of Enhanced Gas Recovery by CO₂ injection (CO₂-EGR) into shale reservoirs has brought increasing attention in the recent decade. CO₂-EGR is a complex geophysical process that is controlled by several parameters of shale properties and engineering design. Nevertheless, more challenges arise when simulating and predicting CO₂/CH₄ displacement within the complex pore systems of shales. Therefore, the petroleum industry is in need of developing a cost-effective tool/approach to evaluate the potential of applying CO₂ injection to shale reservoirs. In recent years, machine learning applications have gained enormous interest due to their high-speed performance in handling complex data and efficiently solving practical problems. Thus, this work proposes a solution by developing a supervised machine learning (ML) based model to preliminary evaluate CO₂-EGR efficiency. Data used for this work was drawn across a wide range of simulation sensitivity studies and experimental investigations. In this work, linear regression and artificial neural networks (ANNs) implementations were considered for predicting the incremental enhanced CH₄. Based on the model performance in training and validation sets, our accuracy comparison showed that (ANNs) algorithms gave 15% higher accuracy in predicting the enhanced CH₄ compared to the linear regression model. To ensure the model is more generalizable, the size of hidden layers of ANNs was adjusted to improve the generalization ability of ANNs model. Among ANNs models presented, ANNs of 100 hidden layer size gave the best predictive performance with the coefficient of determination (R²) of 0.78 compared to the linear regression model with R² of 0.68. Our developed ML-based model presents a powerful, reliable and cost-effective tool which can accurately predict the incremental enhanced CH₄ by CO₂ injection in shale gas reservoirs.

As an effective method to prolong the life of mature field, conformance control in water-injection well has been used wildly. Naturally, effect evaluation of conformance control has attracted great attention because it is an important guideline for the design of later enhanced oil recovery (EOR) plan. Usually, production responses such as excessive water reduction and oil production increment are widely used as the indicators. However, production responses may be unreliable due to the difficulty in determining an effective injection well which is caused by a large number of treated water-injection wells in a well group. Therefore, with the application of fuzzy comprehension evaluation (FCE), five evaluation indexes (injection pressure, injectivity index, slope of hall curve, variation coefficient and homogenization coefficient of injection profile) describe injection responses were selected to establish a new evaluation method in this paper. Based on fuzzy mathematics, FCE reflects the difference of evaluation units. Meanwhile, weights of evaluation indexes were obtained by analytic hierarchy process (AHP), which made the results more convincing. Taking Bai 239 oilfield as an example, the five injection responses indexes were used to assess treatment effect on five water-injection wells by single index evaluation and FCE. The results showed that among the five evaluation indexes mentioned above, the slope of hall curve was the most important factor affected evaluation result. In single index evaluation, opposite results may be produced easily on account of the one-sidedness of single index or human error. Furthermore, we found that effective treatment was a relative concept actually. The result of FCE was consistent with single index evaluation but FCE was more acceptable. This study suggests that FCE could be applied to another field such as water flooding, acidizing and hydraulic fracturing

Rock samples' TOC content is the best indicator of the organic matter in source rocks. The origin rock samples’ analysis is used to calculate it manually by specialists. This method requires time and resources because it relies on samples from many well intervals in source rocks. Therefore, research has been done to aid this effort. Machine learning algorithms can estimate total organic carbon instead of well logs and stratigraphic studies. In light of these efforts, the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and precision. Genetic algorithms, differential evolution, particle swarm optimization, grey wolf optimization, artificial bee colony, and evolution strategies were used to improve machine learning models to predict TOC. The six metaheuristics were integrated into four machine learning methods: extreme learning machine, elastic net linear model, linear support vector regression, and multivariate adaptive regression splines. Core samples from the YuDong-Nan shale gas field, located in the Sichuan basin, were used to evaluate the hybrid strategy. The findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict TOC. The results show that, independent of the metaheuristic used to guide the model selection, optimized extreme learning machines attained the best performance scores according to six metrics. Such hybrid models can be used in exploratory geological research, particularly for unconventional oil and gas resources.

The main objective of this study is to develop the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function. The available semi-analytical infinite-conductivity models (ICMs) for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space (SPS). A new instantaneous source function (i.e., instantaneous uniform-flux segmentary source function under bounded reservoir) is derived to be used instead of SPS to develop the optimal semi-analytical ICM. The new semi-analytical ICM is verified with ICM of Schlumberger [1] and with previous semi-analytical ICMs in terms of bottom hole pressure (BHP) profile and inflow rate distribution along the wellbore. The model is also validated with real horizontal wells in terms of inflow rate distribution along the wellbore. The results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir. Besides that, high computational-efficiency and high-resolution of wellbore discretization have been achieved (i.e., wellbore segment number could be tens of hundreds depending on solution requirement). The results also show that at pseudo-steady state (PSS) flow regime, inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow regime. Therefore, the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying SPS. The optimal semi-analytical ICM is in a general form and real time domain, and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs, of uniform-flux and infinite-conductivity wellbore conditions at any time of well life.

The novelties in this study are as follows:

1. At PSS flow regime:

(1) Inflow rate distribution along the wellbore is stabilized uniform-flux which was verified mathematically.

(2) Primary pressure derivative (PPD) (i.e., PPD = ∂P_Dt/∂t_DA) is equal to (2π/m_t) for any well and reservoir configurations and depends only on half-length wellbore segments number (m_t).

2. The new ICM gives different trend of Bourdet derivative for the first three flow regimes (i.e., early radial, early linear, late radial) and gives the same trend of Bourdet derivative for PSS flow regime, to their counterparts by uniform-flux model (UFM). The trend of pressure derivatives by UFM for any flow regime is well studied in literature, while the counterparts by ICM are new and need detailed study.

The capacitance-resistance model (CRM) has been a useful physics-based tool for obtaining production forecasts for decades. However, the model's limitations make it difficult to work with real field cases, where a lot of various events happen. Such events often include new well commissioning (NWC). We introduce a workflow that combines CRM concepts and kriging into a single tool to handle these types of events during history matching. Moreover, it can be used for selecting a new well placement during infill drilling. To make the workflow even more versatile, an improved version of CRM was used. It takes into account wells shut-ins and performed workovers by additional adjustment of the model coefficients. By preliminary re-weighing and interpolating these coefficients using kriging, the coefficients for potential wells can be determined. The approach was validated using both synthetic and real datasets, from which the cases of putting new wells into operation were selected. The workflow allows a fast assessment of future well performance with a minimal set of reservoir data. This way, a lot of well placement scenarios can be considered, and the best ones could be chosen for more detailed studies.