Lost circulation has been a serious problem while drilling that may lead to heavy financial costs in the form of lost rig time and lost mud fluid. In severe cases, it can lead to well blowout with serious environmental hazards and safety consequences. Despite extensive advances in the last couple of decades, lost circulation materials used today still have disadvantages such as damaging production zones, failing to seal large fractures or plugging drilling tools. Here, we propose a new class of smart expandable lost circulation material (LCM) to remotely control the expanding force and functionality of the injected LCM. Our smart LCM is made out of shape memory polymers that become activated by formation’s natural heat. Once activated, these particles can effectively seal fractures’ width without damaging pores in the production zone or plugging drilling tools. The activation temperature of the proposed LCM can be adjusted based on the formation’s temperature. We conducted a series of experiments to measure the sealing efficiency of these smart LCMs as a proof of concept study. Various slot disk sizes were used to mimic different size fractures in the formation. The API RP 13B-1 and 13B-2 have been followed as standard testing methods to evaluate this product.

Summary: While there have been various lost circulation materials (LCMs) available in the market for treating fractures during the drilling of oil and gas wells, there is still a demand for a technology to seal large fractures. Considering limitations on the size of the particles that can be circulated through the drilling equipment, especially the bottomhole assembly, simply enlarging conventional LCM particles becomes ineffective for sealing large vugs and fractures. In this study, we use shape memory polymers (SMPs) to prepare programmed LCMs with various temporary shapes, which can transform to their permanent shapes with much larger dimensions as compared to their temporary shapes. A series of steps for thermomechanical programming of SMP is designed to trigger their expansion at the reservoir temperature. The dimensions of the programmed shapes can be an order of magnitude smaller than the ones for the original shapes, making their transport through the flowlines feasible, and bridging wide-opened fractures possible. The basic idea is that, after recovery, the SMP-based LCMs form an entangled network across a large width of fracture, and SMP particles recovered within the network, filling in the pores to form an effective sealing. We seek the capability of entangled ladders and interwoven fibers in forming a network across the fracture. A permeability plugging apparatus (PPA) is used to examine the efficiency of developed LCMs. The technique of 3D X-ray computed tomography (CT) is used to visualize the internal structure of formed plugs, enabling us to understand the mechanisms of bridging, plugging, and sealing.

Lost circulation occurs when the returned fluid is less than what is pumped into the well due to loss of fluid to pores or fractures. A lost-circulation event is a common occurrence in a geothermal well. Typical geothermal reservoirs are often under-pressured and have larger fracture apertures. A severe lost-circulation event is costly and may lead to stuck pipe, well instability, and well abandonment. One typical treatment is adding lost-circulation materials (LCMs) to seal fractures. Conventional LCMs fail to properly seal fractures because their mechanical limit is exceeded at elevated temperatures. In this paper, parametric studies in numerical simulations are conducted to better understand different thermal effects on the sealing mechanisms of LCMs. The computational fluid dynamics (CFDs) and the discrete element method (DEM) are coupled to accurately capture the true physics of sealing by granular materials. Due to computational limits, the traditional Eulerian–Eulerian approach treats solid particles as a group of continuum matter. With the advance of modern computational power, particle bridging is achievable with DEM to track individual particles by modeling their interactive forces between each other. Particle–fluid interactions can be modeled by coupling CFD algorithms. Fracture sealing capability is investigated by studying the effect of four individual properties including fluid viscosity, particle size, friction coefficient, and Young’s modulus. It is found that thermally degraded properties lead to inefficient fracture sealing.