M. Anemangely; A. Ramezanzadeh; B. Tokhmechi
Abstract
Achieving minimum cost and time in reservoir drilling requires evaluating the effects of the drilling parameters on the penetration rate and constructing a drilling rate estimator model. Several drilling rate models have been presented using the drilling parameters. Among these, the Bourgoyne and Young ...
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Achieving minimum cost and time in reservoir drilling requires evaluating the effects of the drilling parameters on the penetration rate and constructing a drilling rate estimator model. Several drilling rate models have been presented using the drilling parameters. Among these, the Bourgoyne and Young (BY) model is widely utilized in order to estimate the penetration rate. This model relates several drilling parameters to the penetration rate. It possesses eight unknown constants. Bourgoyne and Young have suggested the multiple regression analysis method in order to define these constants. Using multiple regressions leads to physically meaningless and out of range constants. In this work, the Cuckoo Optimization Algorithm (COA) is utilized to determine the BY model coefficients. To achieve this goal, the corresponding data for two wells are collected from one of the oilfields located in SW of Iran. The BY model constants are determined individually for two formations in one of the wells. Then the determined constants are used to estimate the drilling rate of penetration in the other well having the same formations. To compare the results obtained for COA, first, the two mathematical methods including progressive stochastic and multiple regressions were implemented. Comparison between these methods indicated that COA yields more accurate and reliable results with respect to the others. In the following, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) as meta-heuristic algorithms were applied on the field data in order to determine BY model’s coefficients. Comparison between these methods showed that the COA has fast convergence rate and estimation error less than others.
Omid Saeidi; Ahmad Ramezanzadeh; Farhang Sereshki; Seyed Mohammad Esmaeil Jalali
Abstract
This study aims at presenting a numerical model for predicting grout flow and penetration length into the jointed rock mass using Universal Distinct Element Code (UDEC). The numerical model is validated using practical data and analytical method for grouting process. Input data for the modeling, including ...
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This study aims at presenting a numerical model for predicting grout flow and penetration length into the jointed rock mass using Universal Distinct Element Code (UDEC). The numerical model is validated using practical data and analytical method for grouting process. Input data for the modeling, including geomechanical parameters along with grout properties, were obtained from a case study. The effect of rock mass properties such as joint hydraulic aperture, spacing, trace length, orientation and grout properties as yield stress and water to cement, w/c ratio was considered on grout flow rate and penetration length. To illustrate the effect of aforementioned properties, models were constructed with dimensions of 40×20m. A vertical borehole with diameter of 60mm and 10m depth was drilled in a jointed rock media. The results were in a good agreement with analytical method. It was observed that by increasing joint hydraulic aperture, grouting flow increases using a power law function. The optimum grout penetration observed with joint sets intersection of 40°-60° as experienced in practice. With an increase in joint spacing grout penetration increases around borehole when spacing exceeds two meters it decreases, gradually.
