Abstract

This paper describes a Permian evaporite carbonate gas field that has been plagued by severe water problems since it was put on production in the mid-80s. The field is a carbonate complex consisting of three communicating reservoirs that are heterogeneously fractured. Matrix permeability is typically less than 2 mD, except in one highly permeable streak, where it can be as high as 5 D. The permeability of the natural fracture network is extremely heterogeneous, and varies by up to a factor 100 over the field. Complex interaction between fractures, matrix and the highly permeable streak caused a surprising pattern of water breakthrough, which can be explained by a geomechanical model for the heterogeneous natural fracture network. This predictive, field-wide fracture model was validated and constrained by both geological and flow data.

First, the stress distribution around seismically visible faults was calculated assuming homogeneous, isotropic, linear elastic rock mechanical properties, and frictionless faults. Second, the calculated stress field was used to simulate the growth of discrete fracture networks, which were constrained by statistically comparing fracture orientation and connectivity with that derived from core, BHI, PLT, mud loss, and well test data. Finally, the fracture networks were upscaled dynamically to the grid of a dual-permeability simulator, enabling field-scale multi-phase reservoir simulation. The flow model obtained this way matched historical production data from all wells. It also explained the source of water breakthrough and the inflow profile seen on PLTs. Integrating seismic, borehole, well test and production data to constrain and validate such a field-wide model considerably reduced the uncertainty in the final predictions.

This integrated, predictive fracture model is presently used to investigate future field development scenarios. To this end, the model is coupled to a surface network simulator, which comprises the whole infrastructure. The fully coupled surface and subsurface models offer the flexibility to optimally plan the position and timing of new wells, the size of compressor units, additional in-field trunk lines and the gas offtake.

Introduction

The field consists of three communicating, carbonate reservoirs that are heterogeneously fractured (Figure 1). Each reservoir consists of a dolomite package, sandwiched between two calcite layers. A layer with low matrix porosity and permeability is located in the centre of the dolomite package, and a highly permeable streak of some metres thickness sits between the top calcite and dolomite in only one part of the reservoir. Figure 2 shows the matrix layout, and the well positions. The permeability of the matrix is typically less than 2 mD, except in the streak, where it can be as high as 5 D.

Some wells penetrating this streak experienced water breakthrough in a most unusual way. Water advanced through the streak, but rained out into the fractures below before reaching the wells. Only after some years of production did this fractured matrix become so saturated that water finally entered the well perforations. The timing of water breakthrough in these wells depends on the volume of fractured rock below the streak. Elsewhere in the reservoir the highly permeable streak is absent, and water breakthrough occurs via coning of bottom water, if it occurs at all. Since water production has a high impact in a sour gas environment, knowledge of the fracture distribution and their flow properties is essential for field development.

Fractures are observed in several wells (in cores and FMIs). Some of these are drilling-induced; some are cemented or open natural fractures. The open natural fractures influence flow significantly, as they are more permeable than the matrix by orders of magnitude. Wherever they form a connected network, they constitute a dual-permeability system, with the matrix slowly feeding gas to the highly permeable fractures. A well that taps such a fracture network effectively increases its perforations to the size of the network.

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