Computing True Formation Pressure Using Drilling and Logging Data

Abstract

In order to ensure well stability, distinguish high- and low- pressure zones and estimate the level of pressure depletion, information about formation pressure is necessary. Due to formation damage during drilling and mud filtrate invasion, true formation pressure cannot be measured directly when formation permeability is relatively small. Therefore, an accurate model of invasion profile is required to calculate true formation pressure from formation testing data. This is possible to achieve by combining drilling with LWD and/or wireline logging data. This paper describes a method of computing depth of invasion by inversion of resistivity logging data. We use resistivity image data to calculate flushed zone resistivity and induction logging data to compute true formation resistivity. This, in turn, provides an invasion zone profile and significantly reduces the ambiguity of possible solutions. Drilling regime, rate of penetration, wellhead pressure, and mud properties are used to calculate wellbore pressure. The changes in formation pressure during drilling are computed by the hydrodynamic model of invasion. We present the result of formation testing data processing for water-saturated reservoir. The true formation pressure is estimated using the results of inversion, namely, estimate of mud filtrate volume penetrated into formation. Drilling Mud Invasion During drilling, the pressure overbalance is created to provide well stability and prevent blow-outs. Due to this pressure difference a certain volume of drilling mud filtrate invades the formation. The composition of filtrate is different from that of the formation fluid. Depending on filtration resistance and time of action the depth of invaded zone can vary from a few centimeters to 0.8–1.0 m. Thus, logging measurements with relatively shallow depth of investigation (less than invasion depth) provide information about the disturbed part of the formation and not about the virgin formation parameters. In order to improve interpretation of logging data, it is important to be able to estimate rate of change of formation parameters during drilling. In this paper we present a method to estimate total volume of mud filtrate penetrating into formation. The results are used to improve interpretation of formation testing data. A method to evaluate mud invasion characteristics from resistivity logging data was suggested in Kashevarov et al. (2003). One of the ideas of the method is the change in salt concentration profile due to invasion. It is caused by different salinities of mud and formation fluids and changes in salt concentration and saturation profiles during invasion. This leads to the changes in the resistivity profile. Information about the latter is obtained using resistivity logging data acquired by tools with different depths of investigation. In this paper we used induction and micro-resistivity logging data to calculate the resistivity profile in the near-wellbore zone. The micro-resistivity tool has a very shallow depth of investigation and is therefore sensitive to the flushed zone, which is the nearest to the borehole. Induction logging has much larger depth of investigation and is used mainly to measure true formation resistivity. We use data acquired by both tools simultaneously to define general geoelectric model of the near-wellbore zone. By integrating the two resistivity logging methods we obtain more reliable results and a more detailed resistivity profile.

Dielectric Permittivity Dispersion Measurements in Downhole Conditions – Effect on Porosity Measurements (Russian)

“…Например, можно указать метод скважинного определения пористости в индукционным каротаже с использованием закона Арчи (Karpov et al, 2014;Makarov et al, 2012;Eltsov et al, 2011;Makarov et al, 2010;Gladkikh et al, 2009;Makarov et al, 2009;Antonov et al, 2009;Eltsov et al, 2009;Makarov et al, 2008). Например, можно указать метод скважинного определения пористости в индукционным каротаже с использованием закона Арчи (Karpov et al, 2014;Makarov et al, 2012;Eltsov et al, 2011;Makarov et al, 2010;Gladkikh et al, 2009;Makarov et al, 2009;Antonov et al, 2009;Eltsov et al, 2009;Makarov et al, 2008).…”