Carbonate and sulphide scales can form in CO2 and/or H2S-rich environments in a process which we refer to as "auto-scaling", i.e. these scales form in the produced brine due to a change in conditions such as pressure and temperature, not due to brine mixing. Particularly in production systems, carbonate and sulphide scales can form due to the evolution of CO2 and H2S from the aqueous phase to the gas phase caused by a pressure decrease. Carbonate scale formation in this manner is broadly understood; however, there are details of precisely how this occurs in auto-scaling processes which are not widely appreciated. Measuring the water composition at surface locations (e.g. at the separator) does not give a full indication per se of the amount of scale that has precipitated upstream of the sampling point. However, the composition of the water before precipitation occurs is required for predicting the scaling potential of the system, and this information is seldom available. In this paper, we propose a model that accounts for this issue, and that accurately calculates the carbonate and sulphide scaling profiles in CO2 and/or H2S-rich production systems by knowing only commonly available surface data – i.e. pressure, temperature, and fluid compositions (water, gas, and oil). A rigorous workflow which can do this calculation using any aqueous scale prediction model along with a PVT Model has already been published by the authors (Verri et al, 2017a). The current paper describes a new model to do these calculations which also includes an approach for estimating both the "correct" scaling case within a range of cases up to the "worst case" carbonate scaling scenario. A scale prediction model has been developed to include a three-phase flash algorithm (using the Peng-Robinson Equation of State) coupled with an aqueous electrolyte model (using the Pitzer equations as the activity model). This model is used to run a demonstration example showing the procedure to calculate accurate auto-scaling profiles in CO2 and/or H2S-rich production systems, which is based on building a sensitivity analysis on the ions directly involved in precipitation reactions. We also note that auto-scaling profiles in production systems are commonly obtained by sectioning the production system – either by parameterising depth with pressure and temperature, or by selecting specific locations (e.g. DHSV, wellhead, etc.). Then, established guidelines to treat scale (or not) based on the calculated saturation ratios and precipitated masses of scale can be applied. We show that such an approach is not optimal and that it can lead to under or over-estimation of scale treatments. Furthermore, building on our previous method (Verri et al 2017a) we propose an approach to model the cumulative amount of scale formed under full equilibrium conditions, which is not dependent on how the production system is sectioned. By doing so, the correct amount of scale formed in the production system is always calculated, thus avoiding non-optimum scale treatments. Our approach focuses on calculating the correct auto-scaling profiles in CO2 and/or H2S-rich production systems, and on correctly interpreting the results obtained by thermodynamic modelling and it can be easily integrated with commonly available scale prediction software.
Calcium carbonate (CaCO3) scale can form through an "auto-scaling" process in production systems with a CO2-rich environment due to fluid (water/oil/gas) depressurisation. Thermodynamic modelling is used to estimate the amount and severity of CaCO3 scale precipitation in this context in order to design scale inhibitor or other types of treatments. However, field experience has indicated that thermodynamic calculations often lead to an overestimation of the calcite scale problem. One possible source of this discrepancy may be due to kinetic effects; i.e. that the calcite is somewhat oversaturated (Saturation Ratio, SR >1) but the driving force is not sufficiently large and so the deposition is kinetically "slow". The industry response to this situation has been to come up with some simple heuristics based on field observations, and "rules of thumb" have been developed to account for this apparent overestimation of calcite deposition. The central objective of this paper is to try to address the problem of using such an arbitrary field procedure for calcite scale prediction by introducing the kinetics of calcite deposition in a thermodynamically consistent manner. We view the calcite auto-scaling system as one which moves from SR < 1 (non scaling) incrementally to one that is slightly supersaturated (SR slightly > 1). By making the deposition rate a function of SR, this would give slow rate of deposition initially, but as the system moved into the more scaling regime in the production system (SR > 1) then the deposition rate would increase. However, throughout the system, this kinetic formulation must limit correctly (i.e. it must be consistent with) the underlying equilibrium thermodynamics of the full brine/oil/gas system. Thus, we replace the idea of using heuristic estimates of when calcite scaling occurs by one where an estimate (or measurement) of the kinetics is made; indeed, a range of kinetics rates can easily be run to give an envelope of calcite scaling profiles in the wellbore and throughout the production system. In this paper, we present a model that incorporates a fully consistent kinetic formulation into a general thermodynamic scale prediction model. This model can then calculates scaling profiles in production systems considering both kinetic and thermodynamic effects. In particular, a rate law for the precipitation of CaCO3 based on the respective degree of super-saturation is coupled with the Heriot-Watt FAST Scale Prediction model (HW FAST). HW FAST uses the Pitzer equations and the Peng-Robinson Equation of State to model, respectively, the aqueous and hydrocarbon phases (gas and oil), and it has been developed to calculate CaCO3 scaling profiles caused by a de-pressurisation effect in CO2-rich production systems. First, we present an equilibrium thermodynamic example calculation showing that CaCO3 scale precipitates in CO2-rich production systems due to a de-pressurisation effect, and that precipitation is more severe topsides where the pressure is low than it is downhole where the pressure is high. It is explained that the amount of scale precipitated in this auto-scaling process must be plotted as a cumulative amount, in order to avoid the calculation of a potentially misleading scaling profile. This calculation is then repeated, but also considering kinetic effects for systems with varying temperatures and water flowrates. In the example presented here, we show that this system with sufficiently "low" water flowrates can be approximated by a thermodynamic calculation, and that systems with "high water" flowrates must take kinetic effects into consideration. This scaling profile can then be used to more accurately design scale inhibitor treatments, thus avoiding under or over-treatments (e.g. opting for continuous scale inhibitor injection instead of the more expensive squeeze treatment). Our approach focuses on calculating the correct scaling profile in auto-scaling processes, both qualitatively and quantitatively, by coupling a kinetic formulation to a thermodynamic model, and it can be readily extended to other auto-scaling processes. Further, our kinetic model can be easily integrated with commonly available scale prediction software.
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