Determination of Pressure Dependent Leakoff and its Effect on Fracture Geometry

Barree, R.D.; Mukherjee, Hemanta

doi:10.2118/36424-ms

Cited by 186 publications

(46 citation statements)

References 10 publications

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“…(22), but with different physical constants determining the coefficient C c . However, because these generalizations also lead to v L ∝ (t − t o (x)) −1/2 , the effects can be lumped into a single, composite fluid loss constant C L , which is typically determined from calibration experiments such as diagnostic fracture injection tests (Nolte, 1979;Castillo, 1987;Barree and Mukherjee, 1996) and/or matching model predictions to fracture geometries inferred from microseismic monitoring (Weng et al, 2011b). The resulting form of Carter's leakoff equation is thus given by…”

Section: Carter's Leak-offmentioning

confidence: 99%

Numerical methods for hydraulic fracture propagation: A review of recent trends

Lecampion

Bunger

Zhang

2018

Journal of Natural Gas Science and Engineering

350

172

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Section: Carter's Leak-offmentioning

confidence: 99%

Numerical methods for hydraulic fracture propagation: A review of recent trends

Lecampion

Bunger

Zhang

2018

Journal of Natural Gas Science and Engineering

350

172

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“…Using the Instantaneous Shut-In Pressure (ISIP) from the measured pressure data and the closure stress obtained using the graphical method from G-Function plots (Nolte, 1979) (Barree and Mukherjee, 1996), the net pressure was obtained for each treatment, at the end of each injection. Using this value and the pore pressure data, the Terzaghi minimum principal effective stress (or the fracture closure stress) was also calculated.…”

Section: Fracture Treatment Analysismentioning

confidence: 99%

“…G-Function is a dimensionless time function relating shut-in time after fracture creation to total pumping time and is used to linearize pressure behavior during normal leakoff from a fracture. Barree and Mukherjee (1996) developed idealized curve plots to aid interpretation and Barree et al (2009) summarized methods for closure stress interpretation. Fig.…”

Section: Treatment Analysismentioning

confidence: 99%

Pore pressure effects on fracture net pressure and hydraulic fracture containment: Insights from an empirical and simulation approach

Prabhakaran

Pater²,

Shaoul³

2017

Journal of Petroleum Science and Engineering

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A B S T R A C TPore pressure and its relationship with fracture net pressure has been reported qualitatively from both field and experimental observations. From a modeling perspective, the ubiquitously used pseudo 3D (P3D) models that are based on linear elastic fracture mechanics (LEFM) do not include the effect of reservoir depletion (or overpressure). Models that utilize effective stress as propagation criteria with a cohesive zone description, introduce the pore pressure directly into the simulation and hence can potentially capture the effect of pore pressure on fracture propagation. This work investigates the effect of pore pressure on hydraulic fracturing net pressure and geometry using empirical and numerical simulation approaches. We carried out an analysis of more than 400 datafrac injections spanning a wide range of geological ages and depositional environments in order to investigate the relationship between observed net pressure and reservoir pore pressure. The net fracture propagation pressure from the fracture treatment analysis was seen to be correlated with the effective stress in the reservoir. Fracture propagation simulations were performed using a coupled finite element -finite difference fracture simulator. The code uses a cohesive zone model (CZM) to describe fracture propagation. Four different effective stress scenarios were used to study the effect of effective stress on net pressure. The simulation results closely match the empirical relation between net pressure and effective stress as obtained from the analysis of actual frac treatment data. It is observed from the simulations that the magnitude of the effective stress also has an effect on the fracture geometry with a high effective stress leading to wider, shorter and more radial fractures. The derived empirical correlation is hence useful as a fracture design parameter. The datafrac net pressure diagnostics workflow in the pseudo 3D models can incorporate local tip pore pressure as a new pressure matching parameter. The pore pressure effect can thus explain high net pressures routinely observed in frac operations and also as a containment mechanism.

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“…Castillo (1987) proposed that the fracture closure pressure (taken as an estimate of the minimum principal stress) could be picked at the deviation from linearity of a plot of pressure versus G-time. Later, plots of G×dP/dG were introduced to aid interpretation (Barree and Mukherjee, 1996). If P versus G-time plots as a straight line, then G×dP/dG should also plot as a straight line.…”

Section: Introductionmentioning

confidence: 99%

“…These interpretations of non-ideal transients were developed based on published work by Barree and Mukherjee (1996) and Barree et al (2007) and are widely used in DFIT interpretation (Soliman and Kabir, 2012;Soliman and Gamadi, 2012;Cramer and Nguyen, 2013;Padmakar, 2013;Wallace et al, 2014;Meng et al, 2014;Barree et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Re-examining interpretations of non-ideal behavior during diagnostic fracture injection tests

Jung

Sharma

Cramer

et al. 2016

Journal of Petroleum Science and Engineering

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Re-examining interpretations of non-ideal behavior during diagnostic fracture injection tests, Journal of Petroleum Science and Engineering, http://dx. AbstractDiagnostic fracture injection tests (DFITs) are performed in low permeability formations to estimate the minimum principal stress, formation pressure, permeability, and other parameters. G-function derivative plots are used for diagnosing fracture closure and "non-ideal" reservoir processes. In this study, we use a discrete fracture network hydraulic fracturing simulator to investigate non-ideal DFIT mechanisms. The simulator fully couples fluid flow with the stresses induced by fracture deformation. DFITs are simulated for six different scenarios: a single hydraulic fracture, multiple fracture strands, opening of transverse fractures, near-wellbore complexity, far-field complexity, and height recession. The results indicate that pressure transient behavior commonly ascribed to "fracture height recession," "closure of transverse fractures," and "fracture tip extension" are likely to be misinterpreted by conventional techniques. In previous studies, we found that a curving upward G×dP/dG plot is caused by changing fracture stiffness after closure and that the closure pressure is best picked when G×dP/dG begins to deviate upward. In contrast, the commonly used "tangent" method can significantly underestimate the minimum principal stress. The results of this study confirm those prior results. The results suggest that in most cases, it should be possible to use pump-in/flowback tests to confirm estimates of the minimum principal stress. However, if a flow bottleneck occurs at the wellbore due to near-wellbore complexity, the pump-in/flowback test may be uninterpretable.

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Determination of Pressure Dependent Leakoff and its Effect on Fracture Geometry

Cited by 186 publications

References 10 publications

Numerical methods for hydraulic fracture propagation: A review of recent trends

Numerical methods for hydraulic fracture propagation: A review of recent trends

Pore pressure effects on fracture net pressure and hydraulic fracture containment: Insights from an empirical and simulation approach

Re-examining interpretations of non-ideal behavior during diagnostic fracture injection tests

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