Dynamic modeling of environmental risk associated with drilling discharges to marine sediments

Highlights

• Model: assesses environmental risks from drilling discharges in marine sediments.

• Environmental stressors: oxygen depletion, toxicity, burial and change of grain size.

• Processes: burial, biodegradation, bioturbation processes by diagenetic equations.

• Results: combines temporal evolution of contribution to risk in marine sediments.

• Application: module in SINTEF marine environmental modeling workbench MEMW.

Abstract

Drilling discharges are complex mixtures of base-fluids, chemicals and particulates, and may, after discharge to the marine environment, result in adverse effects on benthic communities. A numerical model was developed to estimate the fate of drilling discharges in the marine environment, and associated environmental risks. Environmental risk from deposited drilling waste in marine sediments is generally caused by four types of stressors: oxygen depletion, toxicity, burial and change of grain size. In order to properly model these stressors, natural burial, biodegradation and bioturbation processes were also included. Diagenetic equations provide the basis for quantifying environmental risk. These equations are solved numerically by an implicit-central differencing scheme. The sediment model described here is, together with a fate and risk model focusing on the water column, implemented in the DREAM and OSCAR models, both available within the Marine Environmental Modeling Workbench (MEMW) at SINTEF in Trondheim, Norway.

Introduction

During offshore drilling operations the vast majority of the waste discharges to the sea are drill cuttings and drilling fluids. Parts of these discharges will remain suspended in the water column while the denser fraction sinks to the seafloor (Neff, 2010). As a result of deposition to the seafloor, adverse environmental effects may be observed in the marine sediments (e.g. Meinhold, 1998). Impacts are primarily due to oxygen depletion (as a result of biodegradation), toxicity of chemicals used in the drilling fluids and physical stress as a result of accumulation of particles on the seabed. Water-based muds (WBM), oil-based muds (OBM), and synthetic-based muds (SBM) are the three main categories of drilling fluids which consist of a base fluid and several chemical components. In addition, the volume of rock cuttings produced during the drilling process may amount to several hundred cubic-meters. Although as the cuttings themselves are non-toxic, there is a potential for burial of organisms during deposition and change of the original sediment characteristics (e.g. grain size distribution) which might cause an alteration of sediment communities. Physical effects of deposition of cuttings on the seabed should therefore be considered in the evaluation of environmental risks in marine sediments (Irvine et al., 2009, Smit et al., 2008a, Smit et al., 2008b, Trannum et al., 2010). Rye et al., 2006, Rye et al., 2008 described the basic equations for calculating the levels of burial of natural sediments, the change of natural grain size, the process of oxygen depletion and toxicity after deposition of drilling discharges. In this paper, we focus on the sediment processes that determine the level of these stressors in the sediment after deposition and how these levels are used for the calculation of environmental risk of drilling discharges.

Early diagenetic processes refer to the physical, chemical, and biological transformations that occur in the surface layer of aquatic sediments following deposition (Berner, 1980, Boudreau, 1997). The theory of early diagenesis is based on the mass conservation of a particular chemical species in the sediment, and is subject to the physical phenomena of burial, bioturbation/dispersion, and degradation. The theory provides a model (i.e. the diagenetic equations) which predicts dynamic concentration profiles of the chemical species in the sediment column.

Diagenetic models have been applied before for environmental modeling and numerous applications and solutions to be found in the literature. Such solutions have been compiled by multiple authors (e.g. van Genuchten and Alves, 1982, Lindstrom and Boersma, 1989, Boudreau, 1997). Moreover one can find further applications of the advection–diffusion–reaction equation for specific conditions. For instance Freijer et al. (1998) have presented an analytical solution to describe leaching and degradation of pesticides in a specific type of column experiment; Kumar et al. (2009) have presented analytical solutions for with variable coefficients. These approaches often include an analytical solution of the diagenetic equation under specific conditions (e.g. steady-state solutions, constant-time invariant model parameters, given initial concentration profiles, specified boundary conditions). However, the diagenetic equation can also be solved numerically, allowing investigators to extend the solutions beyond the limitations of analytical approaches. Boudreau (1997) has reported several different methods and standard computer codes that can be applied. Meysman et al. (2003) investigated complexity and software/code quality of three publicly available models (OMEXDIA, Soetaert et al., 1996; STEADYSED, Wang and Van Cappellen, 1996; CANDI, Boudreau, 1996). These recent generation diagenetic models include all redox zones in the sediment and incorporate extensive species and reactions. Sabeur et al. (2002) attempted to quantify the effect of contaminants on the receiving environment with a so-called long-term model which is an explicit finite difference solution with a forward time/centered space scheme. However, this model ignored any dependency of the governing parameters on environmental impact caused by deposition itself. Rye et al. (2006) developed a sediment model using diagenetic equations to predict the fate of discharges of drill cuttings and mud for the purpose of environmental risk assessment. Following the descriptions from Rye et al. (2006) we developed a methodology to calculate environmental risks in the sediment based on diagenetic equations and incorporated dependency of the controlling parameters.