Funciones del Diagnóstico NCM S

The overall methodology to develop the rehabilitation planning model is shown in Figure 3-14. The model development started with a comprehensive review of the rehabilitation and maintenance types. The rehabilitation techniques are selected after reviewing the maintenance manuals and guidelines for the operation of oil and gas pipelines. The maintenance of oil and gas pipelines is categorized based on their type (i.e., regular maintenance, inspection, remedial actions, repair, and replacement). They are further categorized according to their sizes. Based on the assumption that there is a direct reverse relationship between risk growth and a pipe’s condition during its service life, a

risk-based deterioration profile is developed. As a result, the risk growth profile that is developed in the inspection planning model is reversed to forecast the deterioration of pipes before intervention. This profile is then used to select the required actions of rehabilitation during the life cycle of such pipes.

2- Scenario Development

Define Deterioration Rate

3- Rehabilitation Planning Model

Develop Deterioration Profile Before Interventions Define

Operation Types

Develop Sets of Rules for Interventions Condition

Thresholds

Define Required Maintenance Actions

Develop scenarios (Operations’ type & size)

Operations Cost Estimation (Min., Max. & Mean) Interest Rate Forecast

Define Operations Cost and Interest Rates

Rank Scenarios Based on LCC Amounts

Calculate Condition After Interventions

Identify Common Operation Types

1- Literature Review & Previous Models

Define Cost

Elements Risk-Growth Profile Study Rehabilitation Methods Inspection Planning Model Define Probability of Distribution Functions Monte Carlo Simulation

Parameters Definition

Probability Distribution Function of LCC Compute Min, Max. and Mean

of calculated LCCs Define Functions to Compute

The impact of each rehabilitation type and size on the pipe condition after intervention is studied and a methodology is developed to calculate pipeline condition after rehabilitation. The related cost data is either gathered from previous studies or calculated using the available cost estimates of various repair types. Several combinations of maintenance operation types are considered in the development of the maintenance scenarios. A set of rules are developed to define condition thresholds for the execution of maintenance operation types.

Two types of plans, conservative and regular, are specified. The regular plans impose a set of rehabilitation condition thresholds for different operation types (e.g., coating, repair, replacement) that are lower than those imposed by the conservative ones. Thus, it is the conservative plans that should be used for high-risk pipelines. It is worth noting that the maintenance operations in a conservative plan start sooner than those in a regular one. Each plan is composed of three groups of scenarios. Each group of scenarios is composed of certain types of maintenance operations (i.e., repair and recoat) of various sizes. The condition thresholds specify the time and the type of the necessary maintenance operations. Three groups of maintenance scenarios are considered in each plan. Each scenario group consists of several maintenance scenarios based on the size of the defect. Each maintenance scenario is defined by the following parameters: 1) scenario group; 2) size of the defect; and 3) repair type (i.e., sleeves or clamps).

The required maintenance actions are forecasted by considering the condition of a pipeline before the rehabilitation action and the set of rules for each scenario group. A method is developed to calculate the pipeline condition after each rehabilitation type. The

but also the increment of the condition, which is the improvement in the overall pipeline condition due to a maintenance action. Equations 3.35--3.37 estimate the condition increment of every size of recoat, repair, and replacement, respectively.

CI recoat = 0.5 × (10-OC) ×𝑆₁₀𝑛 (3.35)

CI repair = 0.7 × (10-OC) ×𝑆₁₀𝑛 (3.36)

CI replacement = (10-OC) ×₁₀𝑆𝑛 (3.37)

where “CI” = condition increment for the maintenance operation, “OC” = current overall condition of a pipeline section, and “Sn” = size of the maintenance operation. The term “10 - OC” represents the difference between the current overall condition and the maximum condition of a pipeline, namely, “10” (i.e., the condition of a newly constructed pipeline).

Determining the maintenance operations and their execution time over the life cycle of the pipeline requires the development of deterioration profiles after the rehabilitation interventions for each scenario. Consequently, a profile defines a maintenance scenario and determines the time and type of the maintenance operations that need to be carried out each year. The collected operations’ costs are then used to forecast the cash flow of the pipeline’s maintenance over its life cycle.

Finally, the cash flows of the maintenance scenarios are calculated using Microsoft Excel (Microsoft Group 2010). A Monte Carlo simulation is used to compute the Net Present Value (NPV) distribution function of each maintenance scenario. The probability

distribution functions of the maintenance operation costs and the interest rates are defined using @Risk 6 (PALISADE 2013). The probability distribution functions are used to address the uncertainties in the estimation of the maintenance operation costs and the future interest rates. The distribution functions are defined as triangular functions. The standard parameters of triangular distribution functions are the minimum, maximum, and most likely values, which are defined in the model. After defining the distribution functions of the maintenance operation costs and interest rates, the NPV of each scenario is calculated. For each scenario, the computations on the simulated model are iterated for 1,000 times. The distribution function that best fits the calculated NPV amounts is determined, and the minimum, maximum, and mean values of each scenario are reported. This process is repeated for each scenario. The obtained NPV mean values are used to rank the scenarios. Finally, the scenarios with the lowest NPV values are selected as the optimum maintenance scenarios during the service life of the pipeline.