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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. [ABSTRACT FROM AUTHOR]

Knowing correct values of the rock mechanical properties is crucial for many engineering applications in subsurface. Rocks may show two failure modes during cutting: ductile and brittle. In the ductile mode, rock deforms plastically, and the debris is powdered ahead of the cutting face. On the other hand, chips are the major cutting characteristics for the brittle failure during rock cutting. The critical depth of cut represents the transition point between these two models, so knowing this value helps better predict the failure mechanism of rock. In this paper, a new method is introduced based on measuring the roughness of the groove for determining the transition point of failure modes for every rock sample after the scratch test. The graph depicting the average change in the surface roughness ( R t ) versus the scratched surface roughness ( Δ R ) can be used to identify the rock failure mode and determine the transition point for the cutting process. The value of this slope increases until the depth of cut reaches the transition point, and then the slope reaches a constant value. The main purpose of this paper is to estimate the critical depth of cut of different rock specimens employing the new surface roughness model. [ABSTRACT FROM AUTHOR]

Flowback data is the earliest available data for estimating fracture geometries and the assessment of different fracturing techniques. Considerable attention has been paid recently to analyze flowback data quantitively in order to obtain fracture properties such as effective half-length and effective conductivity by simply assuming fractures having bi-wing planar geometries and constant fracture compressibility. However, this simplifying assumption ignores the complexity of fracture networks. To overcome this limitation, we proposed a semi-analytical method, which can be used as a direct model for fast inverse analysis to characterize complex fracture networks generated during hydraulic fracturing. A two-phase oil–water flowback model with a matrix oil influx for wells with bi-wing planar fractures is also presented to identify limitations of the former solution. Since most available flowback studies use constant fracture properties and the assumption of planar fractures, considering variable fracture properties and complex fracture geometries gives this model more robustness for modeling fracture flow during flowback, more realistically. The proposed models have been validated by numerical simulations. The presented procedure provides a simple way for modeling early flowback in complex fracture networks and it can be used for inverse analysis. [ABSTRACT FROM AUTHOR]