New approaches to model and analyze diagnostic fracturing injection tests

Over the past two decades, Diagnostic Fracture Injection Tests (DFIT), which have also been referred to as Injection-Falloff Tests, Fracture Calibration Tests, MiniFrac Tests in the literature, have evolved into a commonly used and reliable technique to evaluate reservoir properties, fracturing parameters and obtain in-situ stresses. However, the established methods for modeling analyzing DFIT data make two simplifying assumptions: (1) Carter’s leak-off and, (2) Constant fracture compliance (or stiffness) during fracture closure. Both assumptions are violated during fracture closure and this is why G-function based models and subsequent related work can lead to an incorrect interpretation of closure pressure and are not capable of consistently fitting both before and after closure data coherently. In addition, current after-closure analysis relies on impulse solutions with short-term injection assumption and assumes that all injected fluid leaks off into formation. In reality, fluid continues leaking into formation with variable fracture-wellbore system storage, and some injected fluid stay inside wellbore due to pressurization and some stay inside fracture because of residual fracture width. Thus, without considering variable system storage and the associated fluid leak-off, the shortterm impulse solution may introduce significant errors in our interpretation of afterclosure data. In this dissertation, a global DFIT model is developed, which not only preserves the physics of unsteady-state reservoir flow behavior, elastic fracture mechanics, material balance, but also accounts for variable fracture stiffness/compliance and fracture pressure dependent leak-off during fracture closure. For the first time, the before-closure and afterclosure data can be analyzed coherently in a single mathematical model. With our new global DFIT model, we investigated how different mechanisms impact pressure fall-off behavior in a coupled manner. This had been oversimplified in existing literature. In addition, based on this global model, we present a new method to estimate the minimum in-situ stress and to history match DFIT data globally using forward modeling and inverse modeling approaches. New workflows have been proposed to analyze the DFIT data to obtain pore pressure, formation permeability, fracture surface roughness properties and the associated un-propped fracture conductivity. In addition, the normalized fracture conductivity as a function of effective normal stress can be obtained from the DFIT data. Unique pressure fall-off signatures that are associated with naturally fractured reservoirs are presented and discussed, along with representative field cases. Finally, a modified DFIT, rapid injection and fall-off test (RIFT) is proposed to estimate in-situ stress and pore pressure in a single test, without having to shut-in these wells for weeks. RIFT can be used to estimate the minimum in-situ stress in naturally fractured reservoirs with strong pressure-dependent permeability, where DFIT often fails to identify the closure pressure. In addition, the cumulative flow-back volume in the wellbore storage regime on a stiffness plot provides an estimate of the effective fracture volume.