Research On Well Leakage Analysis And Plugging Decision Optimization In Fractured Formations

According to statistics, the economic losses of global oil industry due to lost circulation is over hundreds of millions dollars per year, in which the spent of plugging in fractured formations accounts for more than 90% of the total cost of lost circulation. At present, although there are many description models can quantitatively describe lost circulation, few researches are conducted to the selection of descriptive model combining well leakage logging data. In order to predict the leakage process better and evaluate the severity of leakage, the related study is necessary. The current decision of plugging in fractured formations is made mainly based on empirical methods and semi-empirical method. To make its scientific, it is needed to predict the natural crack width. The existing prediction methods being mainly well logging interpretation, the well logging data leakage prediction methods should be strengthen to make it timely and accurate.Based on the continuity equation motion equation of fluid and the leakage characteristics of drilling fluid in fractured formation, the leakage description models including Newtonian fluid model, Bingham fluid model and power law fluid model both in infinite -long and in finite-long natural fracture are established by using cylindrical coordinates and subsection integration. The influence of different factors on the well leakage in fractured formation are compared by using the leakage description models and the leakage process of Bingham fluid and power-law fluid in two types of natural fractures are simulated, then an optimal selection method of leakage description models is obtained according to the characteristics of loss rate curves. The results showed that the optimized leakage description model can predict the leakage process and evaluate the severity of leakage. The influence law of different factors on the well leakage in fractured formation can provide a theoretical basis for the effective control of well leakage in fractured formation.According to the leakage description model, the width of finite-long natural fracture is solved by using analytic transformation method. For predicting the width infinite-long natural fracture, numerical study on Lietard model is carried out, by which recognize that the theoretical leakage characteristic curves calculated by Lietard model have similar straight line segment; Based on leakage data measured, using the least square method set up the calculation model for the real drilling leakage characteristic curve's similar straight line segment; using adaptive search method find out the real leakage characteristic curve only correspond to the theoretical drilling leakage characteristic curve, by which's dimensionless finite invasion factor we can inverse natural fracture width. After test research:For finite-long natural fracture prediction, Bingham fluid model of implicit solution is obtained and power law fluid model display solution is obtained; For infinite-long natural fracture prediction, the new method for Lietard model is established. Results show that:For finite-long natural fracture prediction, through the formula can quickly and intuitively accomplish its forecast; For infinite-long natural fracture prediction, the new method achieve automatic matching the theoretical leakage characteristic curve without blind spots and overcome human errors, by which control error within 0.001%.Using VS2013 and SQL2008 development tools, the software "well plugging Leakage Analysis and Decision System Software" is developed. This software enables field personnel to calculate and analyze for well leakage correlation and to develop appropriate plugging decision timely when lost circulation occurs in fractured formation, which has the characteristics of promptness, pertinence and science.Research results and software in this article can be used for quantitative and model analysis of lost circulation problems in fractured formations in time. The analysis results will be conductive to putting forward a plugging optimization decisions with pertinence and science and to improving the success rate of plugging operation in fractured formation.