Shale gas reservoirs are unconventional tight gas reservoirs, in which horizontal wells and hydraulic fracturing are required to achieve commercial development. The fracture networks created by hydraulic fracturing can increase the drainage area extensively to enhance shale gas recovery. However, large volumes of fracturing fluid that is difficult to flow back to the surface and remained in the shale formation, will inevitably lead to damages of the shale formations and limit the effectiveness of stimulation. Supercritical water (SCW) treatment after hydraulic fracturing is a new method to enhance shale gas recovery by using appropriate heat treatment methods to the specific formation to convert the retained fracturing fluid into a supercritical state (at temperatures in excess of 373.946°C and pressures in excess of 22.064 MPa). An experiment was conducted to simulate the reaction between shale and SCW, and the capacity of SCW treatment to enhance the permeability of the shale was evaluated by measuring the response of the shale porosity and permeability on SCW treatment. The experimental results show that the shale porosity and permeability increase by 213.43% and 2198.37%, respectively. The pore structure alteration and permeability enhancement of the shale matrix were determined by analyzing the changes in pore structure and mineral composition after SCW treatment. The mechanisms that affect pore structure and mineral composition include oxidative catalysis decomposition of organic matters and reducing minerals, acid-catalyzed decomposition of carbonate minerals and feldspar minerals, hydrothermal catalysis induced fracture extension and cementation weakening induced fracture extension. SCW treatment converts harm into a benefit by reducing the intrusion of harmful substances into the shale formation, which will broaden the scope and scale of shale formation stimulation.
Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow rates. Several correlations have been suggested to model the multiphase flow of oil and gas via surface chokes. However, substantial errors have been reported in empirical fitting models and correlations to estimate hydrocarbon flow because of the reservoir's heterogeneity, anisotropism, variance in reservoir fluid characteristics at diverse subsurface depths, which introduces complexity in production data. Therefore, the estimation of daily oil and gas production rates is still challenging for the petroleum industry. Recently, hybrid data-driven techniques have been reported to be effective for estimation problems in various aspects of the petroleum domain. This paper investigates hybrid ensemble data-driven approaches to forecast multiphase flow rates through the surface choke (viz. stacked generalization and voting architectures), followed by an assessment of the impact of input production control variables. Otherwise, machine learning models are also trained and tested individually on the production data of hydrocarbon wells located in North Sea. Feature engineering has been properly applied to select the most suitable contributing control variables for daily production rate forecasting. This study provides a chronological explanation of the data analytics required for the interpretation of production data. The test results reveal the estimation performance of the stacked generalization architecture has outperformed other significant paradigms considered for production forecasting.
Soil corrosion and hydrogen embrittlement are the main factors of hydrogen pipeline failure. The gas escapes, diffuses and accumulates in the soil and enters the atmosphere when leak occurs. The mechanism of gas diffusion in buried pipelines is very complicated. Mastering the evolution law of hydrogen leakage diffusion is conducive to quickly locating the leakage point and reducing the loss. The leakage model of the underground hydrogen pipeline is established in this paper. The effect of leakage hole, soil type, pipeline pressure, pipeline diameter on hydrogen leakage diffusion were investigated. The results show that when the hydrogen pipeline leaks, the hydrogen concentration increases with the increase of leakage time, showing a symmetrical distribution trend. With the pipeline pressure increase, hydrogen leakage speed is accelerated, and longitudinal diffusion gradually becomes the dominant direction. As the leakage diameter increases, hydrogen leakage per unit of time increases sharply. Hydrogen diffuses more easily in sandy soil, and its diffusion speed, concentration, and range are higher than that in clay soil. The research content provides a reference and basis for the detection and evaluation of buried hydrogen pipeline leakage.
Asphaltene precipitation can result in several production, operational, and transportation problems during oil recovery. If asphaltene precipitates and deposits, it can reduce reservoir permeability, damage wellbore equipment, and plug the pipelines. It is therefore extremely important to evaluate the conditions at which asphaltene precipitation occurs; this is referred to as the asphaltene onset pressure. Asphaltene onset pressure has been measured using many different experimental techniques. There have also been many attempts along the years to predict asphaltene onset pressure using mathematical correlations and models. This research provides an up-to-date comprehensive review of the methods by which asphaltene onset pressure can be measured using laboratory experiments and mathematical models. The research explains the main mechanisms of all the laboratory experiments to measure asphaltene onset pressure under static conditions and how to conduct them and highlights the advantages and limitations of each method. The research also provides a summary of the commonly used mathematical models to quantify asphaltene onset pressure directly and indirectly.
Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water flooding. In this study, the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was investigated.
First, the impact of surfactants on interparticle forces in fine-matrix, fine-fine, and oil-matrix systems was modeled. The results showed that both CTAB (cetyltrimethyl ammonium bromide) and QS (quillaja saponin) cause EDL compaction, weakening the repulsive forces. However, SDS (sodium dodecyl sulfate) and TX (triton X-100) do not affect the EDL. Next, the effect of surfactants on IFT reduction and wettability alteration was experimentally investigated. All surfactants reduced IFT due to the surface excessive concentration mechanism. The wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation, they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil, respectively.
Surfactant aqueous solutions were then injected into various clay-rich sandstone sanpacks, which resulted in increased oil recovery. However, the mechanisms leading to enhanced oil recovery variedby surfactant type. CTAB increased recovery by 10% through IFT reduction and wettability alteration, while SDS and TX increased recovery by 12% and 9%, respectively, through wettability alteration and extreme fine migration. In contrast, partial fine migration in the QS flooding experiment reached a recovery increase of 18%. Permeability trends through experiments were also recorded. During CTAB injection, permeability did not reduce, while QS aqueous solution reduced rock permeability to 5 mD. SDS and TX reduced the magnitude of permeability to 2 mD.
In conclusion, this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces, reducing IFT, and changing wettability. The results suggest that the type of surfactant used should be carefully selected to achieve the desired recovery increase without affecting the permeability of the reservoir.