Numerical Sensitivity Studies for the Joint Inversion of Pressure and DC Resistivity Measurements Acquired with In-Situ Permanent Sensors

Smart Well technology has seen rapid evolution in the last decade because of technological advancements. Proper knowledge of this technology, with some risk mitigating techniques, makes several benefits to an oil company including the capability of drilling longer horizontal and extended reach wells, particularly snake wells with great reduction in cleanup, reservoir management and water and gas breakthrough concerns. Even in some cases unexpected benefits have been discovered from this technology. Sensors are considered to be the heart of smart well completion. There are different types of sensors in the oil industry including wellbore internal sensors and casing external sensors. Some of these sensors are used for wellbore measurement and some for imaging the distribution of reservoir attributes away from the well. In this paper we will investigate all types of sensors either developed sensors and emerging sensors to measure pressure, temperature, flow Rate, noise, phase composition, pH, water cut, gas fraction and capacitance. However commonly used ones are P, T and flow rate sensors. Others are still emerging technologies. It is possible to use permanent sensors named pressure, resistivity, acoustic on outside wall of the casing as well to estimate permeability, porosity, saturation and monitor near wellbore water / flood front encroachment. Although Smart Well technology has shown several benefits but it possesses some challenges regarding their reliability and cost effectiveness and implementation phases. As a result, many companies tend to apply this technology with caution knowing that the cost of a smart completion can easily be three to four times more than a conventional completion. In this paper we present a comprehensive review of state-of-the-art Smart Well technology including all benefits, different types of sensors, challenges, economic consideration and application in fractured reservoir.

show abstract

Petrophysical Properties of Unconventional Low-Mobility Reservoirs (Shale Gas and Heavy Oil) by Using Newly Developed Adaptive Testing Approach

Hadibeik

Chen

Proett

et al. 2012

All Days

View full text Add to dashboard Cite

Pressure testing in very low-mobility reservoirs is challenging with conventional formation-testing methods. The primary difficulty is the over-extended build-up times required to overcome wellbore and formation storage effects. Possible wellbore overbalance or supercharge are additional complicating factors in determining reservoir pressure. This paper addresses the above technical complications and estimates petrophysical properties of low-mobility formations using a newly developed adaptive-testing approach. The adaptive-testing approach employs an automated pulse-testing method for very low-mobility reservoirs and uses short drawdowns and injections followed by short pressure stabilization periods. Measured pressure transients are used in an optimized feedback loop to automatically adjust subsequent drawdown and injection pulses to reach a stabilized pressure as quickly as possible. The automated pulse data is used to determine supercharge effects, formation pressure, and mobility via analytical models by analyzing the entire pressure sequence. A genetic algorithm estimates additional reservoir parameters, such as porosity and viscosity, and confirms results obtained with analytical models (reservoir pressure and permeability). The modeled formation pressure exhibits less than 1% difference with respect to true formation pressure, while the accuracy of other parameters depends on the number of unknown properties. As a quicker method to estimate reservoir properties, a direct neural-network regression of pulse-testing data was also investigated. Synthetic reservoir models for low-mobility formations (M < 1 μD/cp), which included the dynamics of water- and oil- based mud-filtrate invasion that produce wellbore supercharging were developed. These reservoir models simulated the pulse-testing methods, including an automated feedback-optimization algorithm that reduces the testing times in a wide range of downhole conditions. The reservoir models included both simulations of underbalanced and overbalanced drilling conditions and enabled the development of new field-testing strategies based on a priori reservoir knowledge. The synthetic modeling demonstrates the viability of the new pulse-testing method and confirms that difficult properties, such as supercharging, can be estimated more accurately when coupled with the new inversion techniques.

show abstract

Numerical Sensitivity Studies for the Joint Inversion of Pressure and DC Resistivity Measurements Acquired with In-Situ Permanent Sensors

Cited by 4 publications

References 22 publications

An extended Krylov subspace method to simulate single-phase fluid flow phenomena in axisymmetric and anisotropic porous media

An extended Krylov subspace method to simulate single-phase fluid flow phenomena in axisymmetric and anisotropic porous media

Smart well- Benefits, Types of Sensors, Challenges, Economic Consideration, and Application in Fractured Reservoir

Petrophysical Properties of Unconventional Low-Mobility Reservoirs (Shale Gas and Heavy Oil) by Using Newly Developed Adaptive Testing Approach

Contact Info

Product

Resources

About