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- algorithm (1)
- application (1)
- Artificial Intelligence (2)
- ballooning (1)
- borehole (2)
- boundary (1)
- complex reservoir (2)
- cumulative loss (2)
- deformation (1)
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- dip angle (1)
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- drilling fluid (1)
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- elongated fracture (1)
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- formation pore pressure (1)
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- fracture ballooning (2)
- fracture extension (1)
- fractured reservoir (1)
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- pore pressure prediction (1)
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Bektas, Evren (University of Tulsa) | Miska, Stefan Z. (University of Tulsa) | Ozbayoglu, Evren M. (University of Tulsa) | Yu, Mengjiao (University of Tulsa) | Takach, Nicholas (University of Tulsa) | Velazquez-Cruz, David (Instituto Mexicano Del Petroleo) | Shahri, Mojtaba Pordel (Weatherford)

Accurate formation pore pressure prediction is the most important requirement for safe and effective drilling. It essentially contributes to the reduction of drilling risks and provides cost-effective drilling of wells. Even though there are methods that rely on well logs, seismic data and effective stress models to predict pore pressure, there is no model available for real-time pore pressure prediction ahead of the bit.

This study explains how to design and apply a steady-state Kalman filter to predict real-time formation pore pressure optimally by combining outputs from both Eaton's model and from Logging While Drilling (LWD). The objectives of this study are to minimize the noise on pore pressure predicted from well logs (or LWD) measurements and to compute the next estimate of pore pressure ahead of bit using only the most recent measurement.

Data obtained from well logs usually have noise measurements. The noise measurements lead to changes of the results acquired from well logs. Therefore, uncertainties occur on the estimated pore pressure. The designed Kalman filter is a recursive data processing algorithm to produce optimal estimate of pore pressure ahead of the drill bit. The estimates tend to be more refined than those based on measurements from well logs alone.

First, Eaton's method, which is one of the most widely used pore pressure prediction methods, was modeled and represented in the state-space form required for Kalman Filter modeling. Parameters used in the Kalman Filter algorithm were also identified in state-space form. A computer code to implement the designed Kalman filter algorithm has been developed. Additionally, field data were used to evaluate the performance of the proposed algorithm.

Based on the results, it is concluded that Kalman filter can be a very effective tool for detecting overpressure zones to avoid drilling problems before entering such zones.

The most important achievement is that the developed algorithm can be used as a design tool in offshore and onshore drilling operations along with real-time LWD data to optimally estimate the formation pore pressure of the next interval ahead of the bit during the drilling operation.

SPE Disciplines:

Bektas, Evren (University of Tulsa) | Miska, Stefan Z. (University of Tulsa) | Ozbayoglu, Evren M. (University of Tulsa) | Yu, Mengjiao (University of Tulsa) | Takach, Nicholas (University of Tulsa) | Velazquez-Cruz, David (Instituto Mexicano Del Petroleo) | Shahri, Mojtaba Pordel (Weatherford)

Accurate formation pore pressure prediction is the most important requirement for safe and effective drilling. It essentially contributes to the reduction of drilling risks and provides cost-effective drilling of wells. Even though there are methods that rely on well logs, seismic data and effective stress models to predict pore pressure, there is no model available for real-time pore pressure prediction ahead of the bit.

This study explains how to design and apply a steady-state Kalman filter to predict real-time formation pore pressure optimally by combining outputs from both Eaton's model and from Logging While Drilling (LWD). The objectives of this study are to minimize the noise on pore pressure predicted from well logs (or LWD) measurements and to compute the next estimate of pore pressure ahead of bit using only the most recent measurement.

Data obtained from well logs usually have noise measurements. The noise measurements lead to changes of the results acquired from well logs. Therefore, uncertainties occur on the estimated pore pressure. The designed Kalman filter is a recursive data processing algorithm to produce optimal estimate of pore pressure ahead of the drill bit. The estimates tend to be more refined than those based on measurements from well logs alone.

First, Eaton's method, which is one of the most widely used pore pressure prediction methods, was modeled and represented in the state-space form required for Kalman Filter modeling. Parameters used in the Kalman Filter algorithm were also identified in state-space form. A computer code to implement the designed Kalman filter algorithm has been developed. Additionally, field data were used to evaluate the performance of the proposed algorithm.

Based on the results, it is concluded that Kalman filter can be a very effective tool for detecting overpressure zones to avoid drilling problems before entering such zones.

The most important achievement is that the developed algorithm can be used as a design tool in offshore and onshore drilling operations along with real-time LWD data to optimally estimate the formation pore pressure of the next interval ahead of the bit during the drilling operation.

algorithm, application, Drilling, Eaton, formation pore pressure, injector, kalman, Kalman Filter, Kalman filter algorithm, log analysis, permeability, pore, pore pressure, pore pressure prediction, predict pore pressure, prediction, Reservoir Characterization, reservoir geomechanics, Upstream Oil & Gas, well logging

SPE Disciplines:

- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)

**Abstract**

Fracture ballooning usually occurs in naturally fractured reservoirs and is often mistakenly regarded as an influx of formation fluid, which may lead to misdiagnosed results in costly operations. In order to treat this phenomenon and to distinguish it from conventional losses or kicks, several mechanisms and models have been developed. Among these mechanisms under which borehole ballooning in naturally fractured reservoirs take place, opening/closing of natural fractures plays a dominant role. In this study a mathematical model is developed for mud invasion through an arbitrarily inclined, deformable, rectangular fracture with a limited extension. A governing equation is derived based on equations of change and lubrication approximation theory (Reynolds’s Equation). The equation is then solved numerically using finite difference method. Considering an exponential pressure-aperture deformation law and a yield-power-law fluid rheology has made this model more general and much closer to the reality than the previous ones. Describing fluid rheology with yield-power-law model makes the governing equation a versatile model because it includes various types of drilling mud rheology, i.e., Newtonian fluids, Bingham-plastic fluids, power-law, and yield-power-law rheological models. Sensitivity analysis on some parameters related to the physical properties of the fracture shows how fracture extension, aspect ratio and length, and location of wellbore can influence fracture ballooning. The proposed model can also be useful for minimizing the amount of mud loss by understanding the effect of fracture mechanical parameters on the ballooning, and for predicting rate of mud loss at different formation pressures.

Artificial Intelligence, ballooning, borehole, boundary, complex reservoir, cumulative loss, dip angle, drilling fluid chemistry, drilling fluid formulation, drilling fluid property, drilling fluid selection and formulation, drilling fluids and materials, elongated fracture, equation, fracture, fracture aperture, fracture ballooning, fracture extension, gravity force, hydraulic fracturing, loss rate, mud loss, mud loss rate, pressure distribution, Upstream Oil & Gas

SPE Disciplines:

Fracture ballooning usually occurs in naturally fractured reservoirs and is often mistakenly regarded as an influx of formation fluid, which may result in misdiagnosed costly operations. Several models have been developed to treat this phenomenon and distinguish it from conventional losses or kicks. Among these borehole ballooning models and mechanisms, opening/closing of natural fractures is considered to have the main role in naturally fractured reservoirs.

In this study a mathematical model is developed for mud invasion through a disk-shaped and deformable fracture with two impermeable walls and a limited extension. A governing equation is derived based on the lubrication approximation theory (Reynolds's Equation) for radial flow in a single fracture. Considering an exponential deformation law to describe the pressure-aperture relationship, and a yield-power-law model to describe mud rheology, makes this model more general and much closer to the reality than the previous ones. Describing the fluid rheology with yield-power-law model turns the governing equation into a versatile model as it includes various types of drilling mud rheology.

The governing equation is solved numerically using finite difference method. Results show how different parameters can affect fracture ballooning and volume and rate of mud loss/gain. The effects of several parameters related to the mechanical properties of the fracture are analyzed. Shortcomings of the proposed model are outlined.

**1. Introduction**

Drilling through naturally fractured formations causes significant mud loss. The mud loss happens mainly due to the flow into the fractures and a small amount of leak-off into the matrix or wall of the fracture; the leak-off through the matrix depends on the porosity of the matrix but more or less it can be ignored in comparison with the amount of loss through the fractures. Fracture ballooning/breathing or fracture deformation is one of the main mechanisms under which the mud loss/gain occurs while drilling fractured formations. Fracture ballooning corresponds to inflating of a balloon; it occurs when the bottom hole is pressurized and drilling fluid flows into the fracture. Fracture breathing occurs when the rate of mud circulation is decreased and drilling fluid flows out of the fracture. Usually any flow during drilling is interpreted as an influx of the formation fluid and the common cure is to increase the mud weight and to insure an adequate overbalance (Majidi, et al, 2008); but if this influx is due to the mud gain, this kind of treating and controlling not only is not appropriate but also will worsen the situation. Therefore a quantitative analysis of mud gain/loss based on a mathematical model, which describes the physical phenomenon and mechanism under which flow within the fractures happens, is necessary to distinguish mud gain from flowing of formation fluid.

Artificial Intelligence, borehole, complex reservoir, cumulative loss, deformation, deformation law, drilling fluid, equation, Formation Fluid, fracture, fracture aperture, fracture ballooning, fractured reservoir, hydraulic fracturing, mud loss, mud loss rate, rheology, Upstream Oil & Gas, wellbore radius

SPE Disciplines:

Thank you!