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SPE:Fracturing-Fluid Leakoff Under Dynamic Conditions [复制链接]

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只看楼主 倒序阅读 使用道具 0楼 发表于: 2005-10-23 | 石油求职招聘就上: 阿果石油英才网
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Abstract
Laboratory testing of fluid leakoff enables optimum recommendations for fracturing fluid composition in addition to accurate predictions of relationships between leakoff rates and formation and fracturing-fluid properties. Static fluid-loss measurements, the present standardized testing method, provide inadequate results for comparing fracturing-fluid materials or for understanding the complex mechanisms of viscous fluid invasion, filter-cake formation, and filter-cake erosion. Previous dynamic fluid-loss studies have inadequately addressed the development of proper laboratory methods, which has led to erroneous and conflicting results. This paper (Part 1 in a series) discusses the results of a consortium (1989 to 1994) that was established to help us understand and allow modeling of the fluid-leakoff process in hydraulic-fracturing applications. Part 1 summarizes over 300 laboratory experiments structured to study the effects of cell design, fluid-preconditioning (both high-shear and low-shear regimes), and core thickness on fluid leakoff. The results help define appropriate laboratory equipment and testing procedures for realistic modeling of the filtration process of fracturing fluids.IntroductionThe rate of fluid leakoff to the formation during a hydraulic fracturing treatment is one of the most critical factors affecting fracture geometry and treatment performance. The filtration rate during a fracturing treatment affects the designed treatment size, optimal proppant schedule, and resulting proppant distribution within the fracture. Excessive fluid loss may result in insufficient fracture geometry, while low leakoff may result in poor proppant distribution within the fracture as a result of long fracture-closure times. For estimates of fluid leakoff rates, field measurements (commonly known as "minifracs") are required before each main treatment to determine estimates of average filtration rates. Accurate analysis of the minifrac data requires a good understanding of the filtration mechanisms only available through laboratory testing, since leakoff may differ significantly with injection volume. Additionally, the ability to use the minifrac data to estimate filtration rates of other fluids or additives and other well conditions (permeability, temperature, and pressure) is presently not feasible, since these variables may dramatically alter the filtration rates. These difficulties require an understanding of filtration mechanisms that can only be determined from laboratory experimentation.Numerous studies have been performed that attempt to develop acceptable laboratory fluid-leakoff databases; however, significant laboratory variations from poor experimental equipment design and procedures have made developing the required relationships to field conditions unattainable. This paper (Part 1) describes extensive laboratory testing for the development of a reproducible and accurate testing procedure. This paper also addresses classical filtration theory as applied in most fracturing simulators, limitations to the classical theory, previous experimental studies, laboratory equipment and procedures, discussion of results, and conclusions. Discussion of results will be separated into sections on cell effects, fluid preconditioning effects, core thickness effects, and recommendations for a standardized fluid-leakoff testing procedure. Later papers in this series will cover the results of shear rate, permeability, pressure, fluid composition, temperature, fluid-loss additives, and fluid-loss modeling. The first three variables are described in detail in SPE 36493, Part 2 of this series of papers.Classical Filtration TheoryIn the industry fracturing-fluid leakoff is normally modeled with three filtration-resistance coefficients (known as fluid-loss coefficients): (1) the resistance to fluid loss from the filter cake, (2) the resistance to flow in the invasion zone, and (3) compressibility of the noninvaded zone (Fig. 1, Page 12).The noninvaded and invasion-zone coefficients are normally calculated with the expressions in Eqs. 1 and 2 (Page 2). The invasion-zone expression assumes Newtonian-filtrate properties.

Abstract
This paper discusses the results of an industry consortium established to understand and allow modeling of the fluid leakoff process in hydraulic fracturing applications. Over 1,000 laboratory experiments structured to study the effects of shear rate, permeability, differential pressure, temperature, gel concentration, fluid-loss additives, and fluid type have been conducted. Fluid-loss data was measured with a state-of-the-art experimental setup that included fluid preconditioning loops for high shear and low shear regimes and a novel cell design that minimized flow irregularities. Part 2 presents the results of experiments involving linear hydroxypropyl guar (HPG) gel, HPG/borate systems, and HPG/titanate systems at shear rates between 0 and 200 sec-1. pressures between 500 to 10,000 psi, a temperature of 180 F, and core permeabilities between 0.1 md and 1000 md.This study found that fluid loss under dynamic conditions can be significantly higher than under static conditions. Significant differences in fluid-loss behavior were observed between linear gels, transition-metal crosslinked gels, and borate-crosslinked systems. The behavior of linear gels was sensitive to permeability and pressure, but insensitive to shear rate. The behavior of crosslinked gels was more sensitive to shear rate, but less sensitive to permeability and pressure. The fluid loss of all fluids tested could be modeled though the mechanisms of non-Newtonian viscous invasion, classical filter-cake deposition, and filter-cake resuspension. This paper presents guidelines for fluid-loss prediction for these systems with appropriate fluid-loss mechanisms.The findings presented in this paper are vital for the prediction of fracture fluid leakoff within fracture simulators. Understanding which fluid loss mechanism is predominant is essential in analyzing pressure decline data from minifracturing treatments and in using this information in predicting treatment placement.IntroductionTraditionally, hydraulic fracturing has been limited to relatively low-permeability (< 10 md) reservoirs. In recent years, the use of hydraulic fracturing has expanded significantly because of the success of frac-and-pack treatments. As a result, fracturing treatments are now performed in reservoirs with permeabilities up to 1 darcy with beneficial results. The objectives of fracturing low-permeability and high-permeability reservoirs are different and defined by reservoir parameters. In low-permeability reservoirs, the desired objective is typically to obtain a long narrow fracture without obtaining a tip screenout. In high-permeability fracturing, a tip screenout to maximize conductivity is desired. Clearly, understanding the fluid loss is critical in both situations to either prevent or encourage the development of a tip-screenout. Field experience shows that fluid-loss behavior is highly dependent on the reservoir characteristics and is often different from that reported when the standard API tests are used. This discrepancy can be partly attributed to limitations in the standard API procedure and use of static rather than dynamic data. A good summary of the importance of laboratory-measured filtration data and past experimental investigations is provided in the companion paper. A short review of the principal concepts and literature is provided here, followed by an overview of the paper contents.Factors Affecting Fluid Loss of Fracturing Fluids. Experimental data presented in this paper shows that two distinct phases of fracturing fluid loss appear to exist: (1) an early high leakoff phase before a competent filter cake is established across the face of the formation, typically referred to as spurt loss, and (2) a phase where all fluid loss is controlled by the leakoff through the filter cake. The major factors influencing spurt loss and filter-cake behavior are listed as follows:
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