Horizontal Directional Drilling (HDD) has been used internationally for the trenchless installation of utility conduits and other infrastructure. However, the mud loss problem caused by excessive mud pressure in the borehole is still a challenge encountered by trenchless designers and contractors, especially when the drilling crosses through cohesionless material. Investigation of mud loss problem is necessary to apply HDD with greater confidence for installation of pipes and other infrastructure. The main objectives of this research have been to investigate the maximum allowable mud pressure to prevent mud loss through finite element analysis and small scale and large scale laboratory experiments. The recent laboratory experiments on mud loss within sand are reported. Comparisons indicate that the finite element method provides an effective estimation of maximum mud pressure, and “state-of-the-art” design practice- the “Delft solution” overestimates the maximum mud pressure by more than 100%. The surface displacements exhibit a “bell” shape with the maximum surface displacement located around the center of the borehole based on the data interpreted using Particle Image Velocimetry (Geo-PIV) program. A parametric study is carried out to investigate the effect of various parameters such as the coefficient of lateral earth pressure at rest K0 on the maximum allowable mud pressure within sand. An approximate equation is developed to facilitate design estimates of the maximum allowable mud pressure within sand. A new approach is introduced to consider the effects of coefficient of lateral earth pressure at rest K0 on the blowout solution within clay. The evaluations using finite element method indicate that the new approach provides a better estimation of the maximum allowable mud pressure than the “Delft solution” in clay when initial ground stress state is anisotropic (K0 ≠1). Conclusion of this research and suggestions on future investigation are provided. / Thesis (Ph.D, Civil Engineering) -- Queen's University, 2009-01-14 12:23:35.069

Drilling is crucial to many industries, including hydrocarbon extraction, CO2 sequestration, geothermal energy, and others. During penetrating the subsurface rocks, drilling fluid (mud) is used for drilling bit cooling, lubrication, removing rock cuttings, and providing wellbore mechanical stability. Significant mud loss from the wellbore into the surrounding formation causes fluid lost-circulation incidents. This phenomenon leads to cost overrun, environmental pollution, delays project time and causes safety issues. Although lost-circulation exacerbates wellbore conditions, prediction of the characteristics of subsurface formations can be obtained. Generally, four formation types cause lost-circulation: natural fractures, and induced fractures, vugs and caves, and porous/permeable medium. The focus in this work is on naturally fractured formations, which is the most common cause of lost circulation. In this work, a novel prediction tool is developed based on analytical solutions and type-curves (TC). Type-curves are derived from the Cauchy equation of motion and mass conservation for non-Newtonian fluid model, corresponding to Herschel-Bulkley model (HB). Experimental setup from literature mimicking a deformed fracture supports the establishment of the tool. Upscaling the model of a natural fracture at subsurface conditions is implemented into the equations to achieve a group of mud type-curves (MTC) alongside another set of derivative-based mud type-curves (DMTC). The developed approach is verified with numerical simulations. Further, verification is performed with other analytical solutions. This proposed tool serves various functionalities; It predicts the volume loss as a function of time, based on wellbore operating conditions. The time-dependent fluid loss penetration from the wellbore into the surrounding formation can be computed. Additionally, the hydraulic aperture of the fracture in the surrounding formation can be estimated. Due to the non-Newtonian behavior of the drilling mud, the tool can be used to assess the fluid loss stopping time. Validation of the tool is performed by using actual field datasets and published experimental measurements. Machine-Learning is finally investigated as a complementary approach to determine the flow behavior of mud loss and the corresponding fracture properties.