http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Alain P. Tchameni,Lin Zhao,Joseph X. F. Ribeiro,Ting Li 한국자원공학회 2019 Geosystem engineering Vol.22 No.2
Oil-based drilling muds have the greatest preference for drilling operations. However, utilization of environmentally friendly components in drilling mud is fast becoming a requirement prompting production of different types of drilling mud. While there is abundance of prediction models for the rheological properties of oil-based drilling mud, there is scarcity of the same for drilling mud with environmentally friendly additives. In this work, an artificial neural network (ANN) and a multiple nonlinear regression (MNLR) model were developed aimed at predicting the apparent viscosity, plastic viscosity and yield point of waste vegetable oil biodiesel-modified water-based mud. The mean squared errors and correlation coefficient were the key parameters to evaluate and compare the performance of both models. The results indicate that prediction of the ANN perfectly matched the experimental values better than those of MNLR, reflecting its superior performance.
Alain P. Tchameni,Lin Zhao,Robert D. Nagre,Chao Ma 한국자원공학회 2017 Geosystem engineering Vol.20 No.6
This work compares the experimental results of the effects of drilled shale on the formulated oil-in-water emulsion drilling mud using biodiesel produced from waste vegetable oil (WVO) with white oil 5# at 140 °C. The concentration of drilled shale with particle sizes distribution between 80 and 100 mesh was varied from 0 to 16 wt./vol.%. The plastic viscosity, yield point, thixotropy, high-temperature–high-pressure (HTHP) filtration loss, coefficient of friction, and rate of drilled cuttings recovery were assessed. The biodiesel-in-water emulsion drilling mud (BEDM) exhibited better rheological behavior and stability compared to white oil-in-water emulsion drilling mud (WEDM) under the different conditions examined. BEDM demonstrated the lowest HTHP filtration volume with values ranging from 6 to13 cm3 compared to WEDM with 9–18 cm3 and water-based mud (WBM) of 12–25 cm3. Moreover, coefficients of friction of BEDM, WEDM, and WBM were 0.26, 0.35, and 0.75, respectively. BEDM had the highest drilled cuttings recovery rate of 79.60%, followed by WEDM with a rate of 72.80%, while WBM recorded the least (46.25%). Hence, the use of WVO biodiesel as additive in water-based mud can enhance the drilled shale tolerance of water-based drilling mud in an environmentally friendly manner.
Methodology of uncertainty analysis prediction based on multi-well data fusion
Huan Jie Zhang,Kai Wei,Alain P. Tchameni,G. Ben-Kane 한국자원공학회 2018 Geosystem engineering Vol.21 No.3
During drilling activities, geological parameters of a well to be drilled (target well) can be predicted within a limited interval based on multi-well data fusion which aims at ensuring a drilling safety, enhancement of drilling efficiency, reduction of drilling cost as well as acquiring accurate measurements in respect to Oil and Gas protection layers. This work presents a method of uncertainty analysis prediction of pressures using fusion data (formation pressures) from adjacent multi-well. The Eaton method, effective stress theory, and mathematical confidence interval were the various methods used to establish the formation pressure matrix of the target well. The results revealed that due to the complexity and variability of the formations, data interpretation errors of the geological parameters were inevitable. Therefore, the probability density distribution function was established through stratigraphy, probability statistics, and information diffusion. Moreover, the real value of the wells’ formation pressure (target well) was within the distribution interval of multi-well data fusion. Hence, the developed method cannot only effectively reduce the interval of geological parameter of the target well but also enhance the accuracy of parameters prediction.