Coalbed methane (CBM) content is generally estimated using the isotherm theory between pressure and adsorbed amounts of methane. It usually determines the maximum content of adsorbed methane or storage capacity. However, CBM content obtained via laboratory experiment is not consistent with that in the in-situ state because samples are usually ground, which changes the specific surface area. In this study, the effect of the specific surface area relative to CBM content was investigated, and diffusion coefficients were estimated using equilibrium time analysis. The differences in adsorbed content with sample particle size allowed the determination of a specific surface area where gases can adsorb. Also, there was an equilibrium time difference between fine and lump coal, because more time is needed for the gas to diffuse through the coal matrix and adsorb onto the surface in lump coal. Based on this, we constructed a laboratory-scale simulation model, which matched with experimental results. Consequently, the diffusion coefficient, which is usually calculated through canister testing, can be easily obtained. These results stress that lump coal experiments and associated simulations are necessary for more reliable CBM production analysis.
Electrical submersible pump (ESP) operation is compromised by free gas, resulting in premature pump failure and production losses in new wells. It is essential to detect the onset of abnormal operations. We develop a model that predicts abnormal ESP operation when the free gas level increases in the pump. The model compares operation parameters with the parameters of normal operating ranges; it shuts down the ESP when necessary. We used a Schlumberger PIPESIM software (version 2017.01) to perform nodal analysis technique; we tested the model using the other multiphase correlation model and field case studies (where the gas problem in ESP was reported). We employ a homogenous model to calculate the differential pump pressures at various gas volume fractions. Nodal analysis of the intake and discharge point predicted the commencement of abnormal ESP conditions and the associated parameters (critical gas fraction, minimum operating pump intake pressure, and pump discharge pressure). The model results were similar to other surging correlation models (e.g., Romero, Dunbar, Turpin, Cirilo, and Zhou models); they were also identical to field case studies. We identify three performance stability phases when an ESP is exposed to free gas. These are the normal and abnormal operating ranges, as well as the ESP shutdown condition. Modeling permits careful monitoring of ESP operations that can be compromised by free gas.
Most shale gas reservoirs have extremely low permeability. Predicting their fluid transport characteristics is extremely difficult due to complex flow mechanisms between hydraulic fractures and the adjacent rock matrix. Recently, studies adopting the dynamic modeling approach have been proposed to investigate the shape of the flow regime between induced and natural fractures. In this study, a production history matching was performed on a shale gas reservoir in Canada’s Horn River basin. Hypocenters and densities of the microseismic signals were used to identify the hydraulic fracture distributions and the stimulated reservoir volume. In addition, the fracture width decreased because of fluid pressure reduction during production, which was integrated with the dynamic permeability change of the hydraulic fractures. We also incorporated the geometric change of hydraulic fractures to the 3D reservoir simulation model and established a new shale gas modeling procedure. Results demonstrate that the accuracy of the predictions for shale gas flow improved. We believe that this technique will enrich the community’s understanding of fluid flows in shale gas reservoirs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.