Blowout Simulation

This page contains a conceptual description of the blowout engine implemented in Oliasoft WellDesign™.

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Overview

The blowout simulation is employed to estimate the potential blowout rates from reservoirs through designated wellbores to the surface. The surface may be the rig or a platform or it may be the seabed.

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Oliasoft Technical Documentation - Blowout

Model Overview and Application

Area of Application and Limitations

Oliasoft's blowout simulator offers decision support both for environmental risk management in well planning and as basis for worst case discharge for kill evaluations. The simulator takes into account most phases of conventional drilling and the most common flow paths. Oliasoft WellDesign offers a simulator that is user friendly, intuitive and fast allowing the user to perform multiple simulations and a range of sensitivities in order to optimize the well design both from a production and well control point of view. There are however some important limitations on the range of applicability which the user should be aware of. These are listed below.

• The flow simulator assumes steady-state, i.e. fluid properties do not change over time. Reservoir depletion is not taken into consideration.
• For two-phase reservoirs, a mixture of oil and gas is available. Combinations of oil or gas with water is being developed and will be available shortly.
• Flow paths handled are release to Surface/Subsea for Drill string/Annulus/Open hole/Casing. Blowout through the external casing annulus is not handled.
• Cross flow between reservoirs is currently not handled.
• Pressure losses due to acceleration is neglected

Within these restrictions the tool enables analyzing well specific blowout consequences and providing detailed results for the different flow scenarios. The analysis results are given for both oil and gas, and the simulation engine handles multiple reservoirs and multiple fluids in comingled production.

Model Structure

The blowout engine contains two main models:

• Blowout flow rate model, which is based on the following three sub-models
  • PVT model
  • Inflow model
  • Outflow model
• Blowout weighted rate model

The models take input from the user operating the tool. The output from a blowout analysis includes:

• Blowout Flow Rates. Blowout flow rates are computed for all defined scenarios, for both oil and gas. As the model is steady-state, only impact of well kill mechanisms will influence flow rates over time.
• Weighted Blowout Rates. The weighted rates are computed based on probabilities assigned for a range of different scenarios including three flow paths, fully open and partly closed BOP and various reservoir penetration cases.

Modelling Principles and Input Assessment

The simulated blowout rates are used for two purposes. The weighted rates are used, predominantly in the Norwegian sector, as input for drift calculations for environmental studies, and are normally only run for oil fluids.

The user can apply NORSOK recommended probabilities as default or alter the probabilities.

Single blowout rates are used for maximum discharge evaluations and as basis for dynamic kill simulations.

Uncertainties may be assigned to reservoir parameters and Monte Carlo simulations may be run to obtain a probability span of blowout rates.

Probability Assessment

Probability distributions are used as the measure of uncertainty related to reservoir characteristics and the consequences of a blowout. Probability assessment related to scenarios, kill mechanisms and well information is a main activity in the blowout analysis process. Hence, personnel involved in the analysis process or in decision making related to well planning and design must be familiar with how the probability figures shall be interpreted in this context.

Due to field-to-field and well-to-well variations in factors like water depth, lithology, pressure regimes, equipment configurations and drilling procedures the drilling of each well can be considered as a unique process. Consequently, the amount of relevant experience data suitable for supporting probability assessments related to killing a well is scarce. However, by consulting system experts including geologists, mud engineers, drilling managers and other personnel with operational experience, uncertainty can be expressed at a level of detail where system information exists. In order to establish an optimal basis for decision making and planning, the aim is to reach a maximum share of the available information in the analysis, including both the available relevant historical data and expert judgments.

The Blowout Analysis Process

A blowout analysis process should be performed in accordance with the following steps:

1. Assessment of input data
2. Blowout analysis
3. Evaluation of results and decision making related to implementation of candidate measures for consequence reduction

The steps for analysis process are described below.

Input Data Assessment

Assessment of input data is a crucial and considerable part of the blowout analysis process. Some of the input required may be found from relevant documentation related to the drilling operation, e.g. the drilling program. Probabilities and probability distributions, are assigned on the basis of subjective considerations in combination with available experience data.

Experience from pilot studies has shown that work meetings involving personnel from various disciplines help to stimulate constructive discussions and ensure that relevant conditions are included in the considerations in a consistent manner.

Blowout Analysis

After assessing the input parameters required for the blowout analysis, the overall analysis can be performed. The main results from the Blowout simulations include:

• Maximum discharge rate
• Weighted oil rate to surface/seabed

Evaluation of Results

The effect of risk-reducing measures, such as equipment modifications, change of operational routines or increased information of downhole parameters can be represented by proper adjustment of the model input. Re-analyses with adjusted input provide a basis for ranking and selection of candidate measures.

Model Input

General Input Types

The blowout simulation engine requires input on many parameters.

Input Categories

The different input parameters are divided into the following categories:

• Settings Reference information such as rig type, water depth, air gap
• Formation data Pore pressure, fracture gradient, temperature gradient
• Trajectory
• Well bore schematic Casing design, open hole size
• Drill pipe and bottom hole assembly
• Reservoir. Characteristics of the reservoir including:
  • Permeability
  • Pressure and temperature
  • Net pay
  • Permeability
  • Fluid
• Blowout settings Flow path, release point, source reservoir

Input

The reservoir module can be populated manually from scratch, as an individual module separate from the rest of the application, or it can be populated after the data for the formation module, trajectory module, wellbore schematics module and drill pipe module have been input. In that case, the reservoir module will pick correct data from these modules. This input data can always be manually overwritten.

Inflow Performance Relationship

Six different inflow models are available, three for oil and three for gas. These are Oil (combined Darcy-Vogel), Gas deliverability (Forchheimer). In addition, the model allows for user defined PI (productivity index) and user defined IPR curve for both oil and gas. (IPR) [1].

The IPR curve is the relation between the flowing bottom-hole pressure $P_{wf}$ and liquid production rate $q$. Undersaturated oil reservoirs exist as single-phase reservoirs where pressures are above the bubble point pressure. The linear IPR model is given as,

$q = J (P_{res} - P_{wf})$

where $J$ is the productivity index to describe the trends of the IPR curve and $P_{res}$ represents the reservoir pressure.

The solution gas escapes from the oil and becomes free gas when the flowing bottom-hole pressure $P_{wf}$ is below the bubble point pressure $P_b$ [1]. Therefore, Vogel established an empirical equation for two-phase reservoirs in 1968 [2], and it is still widely used in the industry.

If the reservoir pressure $P_{res} < P_b$

$q = q_{max} (1 - 0.2 \frac{P_{wf}}{P_{res}} - 0.8 \frac{P_{wf}}{P_{res}}^2)$

and,

$q_{max} = \frac{JP_{res}}{1.8}$

Otherwise the following is being used,

$q = J (P_{res} - P_b) + \frac{JP_{b}}{1.8} (1 - 0.2 \frac{P_{wf}}{P_{b}} - 0.8 \frac{P_{wf}}{P_{b}}^2)$

As the productivity index $J$ is an unknown variable, it can be estimated according to different flow types.

Oil

Productivity index for oil reservoirs, field units.

$$J = \frac{kh}{141.2 B_o \mu_o (\ln \frac{r_e}{r_w} - 0.75 + S ) }$$

Gas Deliverability

$$J = \frac{kh} T \mu_g Z {141.2 B_o \mu_o (\ln \frac{r_e}{r_w} - 0.75 + S + Dq_g ) }$$

Forcheimer's Model

High velocity flow in porous media is modeled by the Forchheimer equation for gas reservoirs.

$$P_{wf}= P_{res} - a \cdot q - b \cdot q^2$$

Forchheimer equation can be performed for the gas systems, where the nonlinear flow is much more significant, due to the lower gas viscosity which will give high numbers for the same velocity as in liquid systems.

Vertical Lift Performance Relationship

The Vertical lift performance (VLP), known as the outflow model, describes the relationship between the bottom-hole pressure and the flow rate.

The Drift-flux model

The classical drift-flux model for two-phase gas-liquid pipe flow describes the slip between the gas and liquid phases as the combined effect of non-uniform distribution of gas and liquid across the pipe cross section and the additional effect of gas buoyancy as well as local hydraulic gradients near the tip of a Taylor bubble.

The main assumption in the model is that these two effects are additive:

UG = C0 * UM + Ud

Where UG is the gas velocity and UM the mixture velocity given by the sum of the gas and liquid superficial velocities

UM = USG + USL

The distribution coefficient C0 and the drift velocity Ud are often taken to be flow regime dependent, since the physical phenomena they reflect vary widely with the spatial distribution of gas and liquid.

PVT Model

The pressure-volume-temperature (PVT) handling of fluids in many fluid flow simulations describes the phase behavior of gas, oil, and water at different conditions.

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