Graphical Evaluation and Review Technique ("GERT")

Test Your Knowledge

Quiz: Navigating Uncertainty: GERT in Oil & Gas Project Management

Instructions: Choose the best answer for each question.

1. What is the primary advantage of GERT over traditional project management methods like CPM?

a) GERT can handle complex, multi-layered projects with ease. b) GERT allows for the inclusion of conditional and probabilistic relationships within project activities. c) GERT is better suited for projects with a fixed sequence of activities. d) GERT provides a more detailed breakdown of project costs.

2. Which of the following is NOT a benefit of using GERT in oil & gas projects?

a) Realistic risk assessment b) Optimized resource allocation c) Reduced project costs d) Improved decision-making

3. How does GERT contribute to enhanced project control?

a) By providing a detailed timeline for each activity. b) By tracking the progress of activities with varying probabilities. c) By identifying potential bottlenecks in the project. d) By automating project reporting and communication.

4. In the example of an exploration project with two exploratory wells, what does GERT model?

a) The cost of drilling each well. b) The time required to drill each well. c) The conditional relationship between drilling the second well and the outcome of the first. d) The environmental impact of drilling the wells.

5. Which of the following statements about GERT is FALSE?

a) GERT is a valuable tool for managing uncertainty in oil & gas projects. b) GERT can be used to assess project risks and opportunities. c) GERT is only applicable to exploration projects. d) GERT can help optimize resource allocation.

Exercise: GERT in a Gas Pipeline Project

Scenario: An oil & gas company is building a new natural gas pipeline. The project involves several activities, including:

• A: Obtaining permits and environmental approvals
• B: Land acquisition
• C: Pipeline construction
• D: Testing and commissioning
• E: Pipeline connection to the gas network

The project schedule is contingent on several factors, including:

• The approval process for permits may be delayed due to unforeseen circumstances.
• The land acquisition process can be influenced by potential legal challenges.
• The construction timeline is dependent on weather conditions.

Task:

1. Identify the conditional and probabilistic relationships between the activities.
2. Create a simple GERT network diagram representing the project. You can use basic symbols like squares for activities and arrows for dependencies.
3. Briefly explain how GERT could be used to manage the uncertainties associated with this project.

Techniques

Chapter 1: Techniques

The Essence of GERT: Beyond the Linear Path

GERT (Graphical Evaluation and Review Technique) differentiates itself from traditional project management methods like CPM (Critical Path Method) by embracing the inherent uncertainty and complexity of projects, particularly in the oil and gas industry. Unlike CPM's fixed sequence of activities, GERT introduces a probabilistic and conditional approach, allowing for more realistic project planning and execution.

Key Concepts:

• Conditional Relationships: Activities in a GERT network are linked through conditional relationships, meaning their execution depends on the outcome of preceding activities. For example, drilling a second well might be contingent on the success of the first exploratory well.
• Probabilistic Activities: GERT accounts for the likelihood of activities being completed, acknowledging that not all activities have a guaranteed outcome. This is particularly relevant in exploration phases where the success rate of finding viable deposits is not certain.
• Network Representation: GERT uses a network diagram to visually represent the relationships between activities. Nodes represent activities, and arcs represent the connections between them, including conditional dependencies and probabilities.
• Simulation and Analysis: GERT models can be simulated to generate different project scenarios, providing insights into potential outcomes, project durations, and resource requirements under various circumstances.

Comparing GERT with CPM:

| Feature | CPM | GERT | |---|---|---| | Activity Sequence | Fixed, predetermined | Conditional, probabilistic | | Uncertainty | Ignored | Explicitly considered | | Network Type | Linear | Network with branches and loops | | Analysis Focus | Critical path, shortest duration | Probabilistic outcomes, risk assessment |

GERT's ability to handle uncertainty and conditional relationships makes it a powerful tool for planning and managing complex projects in the oil and gas industry where unpredictability is a constant factor.

Chapter 2: Models

Building the Framework: GERT Network Models

Creating a GERT network model involves several steps, each crucial for capturing the intricacies of a project and effectively simulating potential outcomes:

1. Define Activities:

• Break down the project into individual activities. Each activity represents a discrete task or process within the project.
• Identify dependencies: Determine which activities must be completed before others can begin.
• Assign probabilities: For each activity, estimate the probability of its successful completion.

2. Construct the Network:

• Nodes: Use nodes to represent each activity within the network.
• Arcs: Connect nodes with arcs to represent the relationships between activities.
• Conditional Arcs: Use conditional arcs to represent dependencies between activities, indicating that an activity can only proceed if a specific preceding condition is met.
• Probabilistic Arcs: Label arcs with probabilities to represent the likelihood of an activity being completed successfully.

3. Define Events:

• Start Event: The initial node where the project begins.
• End Event: The final node representing project completion.
• Intermediate Events: Represent decision points or milestones within the project.

4. Model Parameters:

• Activity Duration: Assign an estimated duration to each activity, taking into account the probability of success.
• Resource Requirements: Specify the resources (labor, equipment, materials) needed for each activity.
• Cost Estimates: Assign cost estimates to each activity.

5. Simulation and Analysis:

• Simulate the network: Run the GERT model using computer simulations to generate multiple project scenarios.
• Analyze outcomes: Examine the resulting data to understand the probabilities of different project outcomes, including project duration, costs, and resource usage.
• Optimize decisions: Use the analysis to inform project decisions, adjust schedules, and allocate resources effectively.

Chapter 3: Software

Tools to Power GERT Applications:

The complexity of GERT models necessitates dedicated software to efficiently manage network construction, simulation, and analysis. Several software tools have emerged to facilitate GERT applications, including:

1. GERT Simulation Software:

• Specialized GERT packages: Some software packages are specifically designed for GERT modeling and simulation. These packages provide built-in features for network construction, probability assignments, and analysis of simulation results.
• General simulation software: General-purpose simulation software can also be used to create and simulate GERT models. Features for discrete event simulation, network modeling, and statistical analysis are essential.

2. Features to Look For:

• Graphical Interface: User-friendly interfaces with drag-and-drop functionality for network construction and visualization.
• Simulation Capabilities: Advanced simulation engines for efficient and accurate generation of project scenarios.
• Data Analysis Tools: Features for analyzing simulation results, generating reports, and visualizing data.
• Customization Options: Flexibility for adjusting model parameters and defining custom scenarios.

3. Popular Software Options:

• GPSS/H: A widely used simulation language with robust features for discrete event simulation and network modeling.
• Simul8: A simulation software package designed for process improvement and optimization, offering GERT modeling capabilities.
• AnyLogic: A powerful simulation software with comprehensive features for GERT modeling and analysis.

Choosing the right GERT software depends on project specific requirements, budget constraints, and the desired level of sophistication in modeling and analysis.

Chapter 4: Best Practices

Maximizing GERT for Project Success:

Effective implementation of GERT requires adherence to best practices to ensure accurate modeling, efficient analysis, and valuable insights for decision-making:

1. Clear Project Definition:

• Precise Scope: Define the project scope clearly, outlining specific goals, deliverables, and timeframes.
• Activity Decomposition: Break down the project into manageable, clearly defined activities with defined inputs and outputs.
• Stakeholder Involvement: Engage relevant stakeholders to ensure comprehensive understanding of project requirements and constraints.

2. Comprehensive Data Collection:

• Accurate Probabilities: Collect historical data and expert opinions to establish reliable estimates for activity probabilities.
• Realistic Durations: Assign realistic durations to activities based on historical data, expert estimates, and resource availability.
• Resource Allocation: Assess resource requirements for each activity and consider potential resource constraints.

3. Iterative Modeling and Analysis:

• Initial Model: Create a preliminary GERT model to capture the key relationships and dependencies.
• Refine and Adjust: Use the initial model to simulate and analyze the project. Refine the model based on the results and insights gained.
• Sensitivity Analysis: Conduct sensitivity analysis to assess the impact of uncertainties on project outcomes, identifying critical parameters that require closer attention.

4. Communication and Collaboration:

• Transparency: Clearly communicate the rationale behind GERT model assumptions and the implications of simulation results.
• Team Involvement: Involve relevant stakeholders and project team members in the model development, simulation, and analysis process.
• Decision Support: Use GERT insights to inform project decisions, but recognize that it's a tool for analysis, not a replacement for informed judgment.

By following these best practices, GERT can become a valuable tool for enhancing project planning, risk management, and decision-making in the oil and gas industry.

Chapter 5: Case Studies

GERT in Action: Real-World Applications in Oil & Gas:

To demonstrate the practical value of GERT in oil and gas project management, here are a few illustrative case studies:

1. Offshore Exploration Project:

• Challenge: A company planned to drill multiple exploratory wells in a challenging offshore environment. Success rates were uncertain due to geological complexities and potential weather delays.
• GERT Implementation: A GERT model was developed to simulate different drilling scenarios, accounting for the probabilities of well success and potential delays due to weather or technical challenges.
• Outcome: The model helped the company assess the overall project risk, identify critical factors influencing project duration, and adjust resource allocation based on the simulated outcomes.

2. Gas Pipeline Construction Project:

• Challenge: A pipeline construction project faced potential delays due to regulatory approvals, environmental permits, and land acquisition complexities.
• GERT Implementation: A GERT model was built to simulate the project, incorporating probabilities for obtaining approvals and the potential impacts of delays on overall project schedule.
• Outcome: The model enabled the project team to anticipate potential delays, identify critical path activities, and develop contingency plans to mitigate the impact of uncertainties.

3. Refinery Expansion Project:

• Challenge: A refinery expansion project involved multiple interconnected activities with varying probabilities of success and potential for delays.
• GERT Implementation: A GERT model was created to simulate the project, capturing the dependencies between activities and the likelihood of completing them within budget and schedule.
• Outcome: The model provided valuable insights into the project's critical path, potential delays, and resource allocation strategies, enabling the team to make informed decisions and mitigate risks.

These case studies highlight how GERT can be successfully applied to various aspects of oil and gas projects, offering a powerful tool for managing uncertainty, improving decision-making, and increasing project success rates.