Abstract

The advent of subsea wells, production from ever-deeper waters, and the resulting increase in value of wells and downhole equipment means that more effort is being put into assessing the risks posed by potential scale formation. This is required not only because of the increasing value of the investment that needs to be protected, but also due to the increasing difficulty in accessing wells to treat them. It is becoming widely recognized that an integral part of the scale risk assessment process involves calculating fluid flow in the reservoir. These calculations enable the operator to identify where in the reservoir scale may form, how these zones develop as a function of time, and where they are located relative to the production wells. If scale forms deep within the reservoir, then typically there is no loss of productivity, and indeed the effect is beneficial in that it reduces the scaling potential at the production wells. However, if scale deposition should be expected close to the production wells, then steps should be taken to mitigate any harmful effects. The choice of management strategy will depend on the type and severity of the scaling problem, and the access to the wells requiring protection.

A range of flow simulation tools is studied. These vary from standard finite difference reservoir simulators to streamline models designed specifically to track the flow path of injected waters, to more complex fluid flow and chemical reaction models capable of calculating scale precipitation reactions and the subsequent impact on porosity and permeability. Field examples are then given of situations in which these models have been applied, and the implications for scale management of the resulting calculations are discussed.

Introduction

The deposition of inorganic scales is a flow assurance issue associated primarily with the production of water1–4. The potential extent of scale formation is determined by two principal factors:

  1. The temperature, pressure and chemical composition of the brines in the reservoir;

  2. The volumes of scaling brines being produced.

Scale prediction codes are routinely used to calculate the potential mass and scaling tendency of the produced brines. When account is taken of the expected volumes of produced water, a basic scaling risk may be evaluated. However, an oilfield reservoir under production is a dynamic system, and thus the temperature, the pressure, the chemical composition of the brines, and the volumetric flow rates may all vary from location to location within the reservoir, and will probably also with time. Therefore, the potential for scale formation and damage to productivity will also vary with time. Furthermore, scale precipitation in situ deep within the reservoir may impact the scaling potential at the production wells. Thus, to properly assess the risk of scale damage over a field's life cycle it is necessary to account for the changes in fluid properties in the reservoir with time.

Although never perfect, the best estimate of how fluid conditions will vary with location and time may be obtained from the dynamic reservoir simulation model. Reservoir simulations are usually performed to predict and optimise hydrocarbon recovery. Thus, considerable effort is often put into making these calculations as accurate as possible, as important operational decisions relating to the extraction of hydrocarbons may be influenced by the results. However, even the most generalised models may also be used to study, and to an extent to quantify, the scaling risk potential5–6. More complex models may also be used to model the precipitation of scale in situ7–11, allowing for a more accurate prediction of formation damage, and a better understanding of how flow behaviour in the reservoir affects the scaling risk at the production wells.

This paper briefly outlines the relevant mechanisms of scale formation, and then discusses the three most common types of reservoir simulation model used to quantify scale risk, what they can and cannot be used to calculate, and what are their principal advantages and disadvantages.

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