Coal Seam Gas Extraction by Integrated Drillings and Punchings from the Floor Roadway considering Hydraulic-Mechanical Coupling Effect

Owing to the exhaustion of shallow coal resources, deep mining has been occupied in coal mines. Deep buried coal seams are featured by the great ground stress, high gas pressure, and low permeability, which boost the risk of gas disasters and thus dramatically threaten the security about coal mines. Coal seam gas pressure and gas content can be decreased by gas extraction, which is the primary measure to prevent and control mine gas disasters. The coal mass is simplified into a continuous medium with dual structure of pores and fractures and single permeability. In consideration of the combined effects of gas slippage and two-phase flow, a hydraulic-mechanical coupling model for gas migration in coals is proposed. This model involves the equations of gas sorption and diffusion, gas and water seepage, coal deformation, and evolution of porosity and permeability. Based on these, the procedure of gas extraction through the floor roadway combined with hydraulic punching and ordinary drainage holes was simulated, and the gas extraction results were used to evaluate the outburst danger of roadway excavation and to verify the engineering practice. Results show that gas extraction can reduce coal seam gas pressure and slow down the rate of gas release, and the established hydraulic-mechanical coupling model can accurately reveal the law of gas extraction by drilling and punching boreholes. After adopting the gas extraction technology of drilling and hydraulic punching from the floor roadway, the remaining gas pressure and gas content are reduced to lower than 0.5 MPa and 5.68 m3/t, respectively. The achievements set a theoretical foundation to the application of drilling and punching integrated technology to enhance gas extraction.

Reasonable Layout of High Drainage Roadways for Jiaojiazhai Mine

To ensure that the gas concentration at the top corner does not exceed the limit, a reasonable level of the high drainage roadway layout in Jiaojiazhai Mine should be determined. In this work, based on the actual conditions of the working face, an SF6 tracer gas was used to test the connectivity between the high drainage roadway and the working face. A discrete element analysis program was used to simulate the deformation law of the overlying strata in the goaf, and a corresponding caving control program for the surrounding rock was written based on the obtained parameters and “O” ring theory. A fluid simulation software was used to simulate and analyze five goaf models with different high drainage roadway layouts (10, 15, 20, 25, and 30 m). The gas drainage data for two layers (10 m and 20 m) of the high drainage roadway were measured. The results showed that the height of the caving zone in the goaf is approximately 20 m, and when the high drainage roadway is arranged along the roof (when the layout layer height is 10 m), the roadway will be directly connected to the working face, thus pumping fresh air to the working face. The gas extraction effect of the 20 m stratum was better than those of the other strata. The simulation results of the gas extraction were consistent with the measured data. The proposed scheme was practically applied, and its effect was found to be evident, thus solving the problem of high gas concentration at the top corner and increasing the mine output.

Groundwaters in Northeastern Pennsylvania near intense hydraulic fracturing activities exhibit few organic chemical impacts

Hydrogeologic transport contributes to limited organic chemical contamination in a region of intense gas extraction, even 10 years post-development.

Energy Harvesting Under Harsh Conditions for the Oil & Gas Upstream Industry

Environmental and safety sensing is becoming of high importance in the oil and gas upstream industry. However, present solutions to feed theses sensors are expensive and dangerous and there is so far no technology able to generate electrical energy in the operational conditions of oil and gas extraction wells. In this paper it is presented, for the first time in a relevant environment, a pioneering energy harvesting technology based on nanomaterials that takes advantage of fluid movement in oil extraction wells. A device was tested to power monitoring systems with locally harvested energy in harsh conditions environment (pressures up to 50 bar and temperatures of 50ºC). Even though this technology is in an early development stage this work opens a wide range of possible applications in deep underwater environments and in Oil and Gas extraction wells where continuous flow conditions are present.

Assessing and predicting individual occupational risk and determining its exact categories using probabilistic methods

Existing approaches to occupational risk assessment more often involve evaluating its group levels and individual risks are assessed less frequently. These approaches provide deterministic risk assessment which doesn’t take into account uncertainty in risk categorizing when its values are close to boundaries between adjoining risks categories. It substantiates the necessity to assess occupational risk levels using probabilistic methods. Our research object was occupational risk and the basic subject was distribution of individual occupational risk levels among workers. Our test group was made up of oil and gas extraction operators exposed to noise equal to 80–85 dBA at their workplaces (173 people). Our control group included oil and gas extraction operators and engineering and technical personnel occupationally exposed to noise equal to 60–77.8 dBA (259 people). We performed a priori assessment of occupational health risks; accomplished epidemiologic analysis of a cause-effect relation between health disorders and work; calculated group occupational health risks; calculated and predicted individual occupational risk using mathematical modeling of dependence between probable negative responses and working conditions, age, and period of employment; determined risk categories more precisely using fuzzy sets by calculating the membership function. As a result, we established that proven individual risk levels were distributed unevenly (1.06•10-4–1.47•10-2) as per categories within a group characterized with a suspected average risk level. A category of proven individual risk levels was determined more precisely using fuzzy sets; after that distribution of probability of their membership was evaluated to detect that at the moment of the research a share of workers with their proven individual occupational risks falling into lower risk categories (p > 0.5) amounted to 89.6 %. We attempted to predict risks for the whole employment period given that working conditions remained the same and no prevention activities were provided. Our prediction revealed that individual occupational risks would remain unacceptable for all workers in the test group and would amount to 2.53•10-2–3.51•10-2; a risk category was also expected to become higher. In-dividual occupational risk would be categorized as average for most workers and as high for 23 % of them (p < 0.5).