Characterization of a Volcanic Formation Through Comprehensive Well Test Analyses

Abstract

Abstract It is generally difficult to uniquely estimate the layer properties of a stratified reservoir by using pressure-transient data alone as a practical matter. Some additional data such as downhole flow rates for each layer are required for the analyses. Combined analyses of pressure-transient data with production logging surveys are successfully performed in a large gas field of thick volcanic reservoir in Japan, where some wells exhibit heterogeneous behavior during well tests. The consistency throughout the analyses ensures the reliability of matched model which can support a characterization of the reservoir. The importance of performing a production survey in a proper time period by an inspection of diagnostic plots prior to the survey is also addressed. A systematic and comprehensive approach presented in this paper is applicable to any thick formation with vertical heterogeneity. Introduction Large hydrocarbon deposits occur in deep-seated volcanic rocks of the Middle Miocene age in the Minami Nagaoka gas field onshore Japan. As a consequence of repeated volcanisms, rhyolite eruptions were deposited one after another forming a thick formation with a rapid change of rock facies which resulted from drastic chilling and shattering in submarine volcanism. The reservoir rock, mainly composed of the rhyolite, is divided into three facies as follows:Hyaloclastite facies, where drastic chilling and spalling of magma by sea water is most evident,Lava facies of massive nature, which was not affected by the drastic chilling and spalling since it is believed to be located in the core of the rhyolite body, andPillow breccia facies which, intermediate between the two, is most favorable as a reservoir rock. The reservoir has total thickness of more than 2,600 ft occurring at a depth of 12,500 ft and deeper below surface, with the initial reservoir pressure of 8,100 psi and temperature of 350 F. Core analyses show that the permeability of pillow breccia facies ranges from 0.1 to 10 md while most of the hyaloclastite facies yields low values of less than 0.1 md, though the average porosity is around 15% in both facies. Lava facies is characterized by a lower average porosity value of less than 10% but, as for permeability, some core samples show values of larger than 1 md. Permeability plotted versus porosity widely scatters even within the same facies, and there exists no obvious correlation between permeability and porosity. Thus, the porosity distribution estimated through well logs cannot be converted to a permeability distribution. Core samples may be used to establish such a distribution for cored intervals of certain wells, but they do not cover whole intervals. Because of these limitations, the permeability distribution with depth in the subject reservoir is not well defined. However, the rapid change of rock facies and well log responses as shown in Fig. 1 suggests the occurrence of drastic variation of formation properties including permeability with depth, and even with lateral distance in the reservoir if considering the origin of the rock. As is expected from the situations described above, some of the wells drilled in this field yield heterogeneous behavior during well tests, to which several interpretations are possible and no unique reservoir model can be determined through the limited information of pressure-transient data. To overcome this difficulty another set of information is desired, and production logging surveys are conducted during production and shut-in periods for a well that yields heterogeneous behavior during well tests. Through production logging, formation properties that ensure the uniqueness of well test analyses are obtained. This paper shows how the production logging data should be pre-processed and describes the comprehensive approach that combines pressure-transient analyses and production logging analyses to characterize the thick volcanic formation with severe heterogeneity. A layered reservoir model that explains the pressure behavior and the quantitative nature of the crossflow through wellbore is presented. P. 243^