Background
As a source of non-renewable energy, oil and gas are considered as extremely valuable resources for many countries whose economy rely mainly on petroleum (Esmaeili et al. 2015). The selected case study is for a gas injection project carried out by an oil and gas company in one of the oil fields in the Sultanate of Oman. Basically, production rate of oil from oil well will be at its peak in the beginning of the production cycle. However, slowly the production rate will start diminishing. At that instance, to enhance oil recovery from oil and natural gas wells, secondary production methods were employed. Gas injection is one of those methods and is widely used in oil and gas industry.
The project’s nature is risky as it involves processing very toxic fluids at high pressure. In addition of being toxic, the gas is highly corrosive. This toxicity and corrosiveness is due to the high concentrations of H2S and CO2. In addition to the highly risky nature of the processed fluid, the proposed facilities are to be constructed in brown field, i.e. to be installed within the existing facility adding complexity to the construction activity. The scope of the gas injection project includes installing the following units:
-
Gas dehydration unit through the use of Tri-Ethylene Glycol (TEG). The unit will dehydrate injection gas to reduce the water content and hence minimize the use of corrosion resistance alloys (CRA) as material of construction.
-
High-pressure injection compressor to boost the dehydrated gas pressure to the required injection pressure set by the reservoir engineers.
-
High-pressure transport system consisting of high-pressure pipeline transferring injected gas from the compressor discharge to the injection wellhead.
-
Gas injection wells.
-
Piping modification within the existing facility.
-
Providing the required utilities.
Risk analysis model
Figure 1 presents the flow chart of the process followed in this study in an attempt to manage risk within the project. From Fig. 1, it is seen that the process flow chart consists of four components, namely company input, model construction, running simulation and then results. Details of the flow chart are explained below.
Company input
Cost estimate
The project cost estimate was developed by the company cost-engineering department based on the company database. The project’s cost estimate includes base cost, contingency cost, cost to cushion the effect of future market condition and escalation. Table 3 summarizes the main items in the cost estimate:
Table 3 Project’s cost estimation
Project schedule
The project team’s planning engineer with the input from the project engineer has prepared the project’s schedule. At this stage of the project, level 4 schedule has been prepared. However, for the objective of this study, level 3 has been used as level 4 is very detailed and covers over 1700 activity.
Risk register
Basically, risk register consists of brief description about the risks associated with the project, its likelihood and impact on the project. Risk register may be qualitative or it may be quantitative. Qualitative risk register is the one where the likelihood of occurrence of risk are estimated by ranking them as “high” to “low”. On the other hand, if the likelihood of occurrence is put in the form of probabilistic number then it is known as quantitative risk register. In this research both qualitative as well as quantitative analysis has been carried out. Risk register starts with the identification of risk.
Risk identification
The risks involved in the project under consideration were identified through field visit, interview with the workers and consultation with site engineers. Also, project team was requested to brainstorm all the potential risk factors. Following 16 factors were identified as the risks involved in this project that leads to cost overrun or delay in the schedule or both of them.
-
1.
Working adjacent to existing live plant leading to exposure to high H
2
S gas The high H2S content in the processed gas adds complexity to the construction activities, as it requires limiting the capacity of the construction crew, trained crew with safety procedures and longer shutdown durations. In addition to the delay, fatality may occur due to H2S exposure.
-
2.
Lack of installation and commissioning spares leads to delay in start-up In many instances, ordering spares parts is overlooked or due to transport/storage, they are lost resulting in delays.
-
3.
Footprint specified in the plot plan is not met by the package Vendors resulting in delay in Engineering Sometimes there is a mismatch between footprint area specified by the equipment vendor and between what has been considered by the engineering consultant. This would result in re-work of some of the engineering activities and hence delay in the preceding activities.
-
4.
Pipe and pipe fittings of 10,000#: Sourcing from mill and expected delay due to small quantity The high-pressure rating pipes are to be installed downstream the injection compressor up to the injection wellhead. Since the quantity to be ordered is relatively small, the order is expected not to be very attractive to the manufacturer and hence delay is likely to occur.
-
5.
Complex interfaces within package vendors leading to delay in delivery of vendor packages resulting in project delay The project has number of interfaces, which have to be managed. The risk arises due to having different parties working in their scopes in isolation and leaving the interfaces with poor definition. For example, any changes within the TEG unit will affect the quality of the dehydrated gas and hence the design of the injection compressor.
-
6.
Failure of Vendors to comply with approved designs resulting in delay Sometimes the vendor will propose materials which are not approved by the project.
-
7.
Failure during acceptance testing resulting in delays Vendors have to prove that their equipment delivers the approved design by testing it at factory and site conditions. Failures can be minor or severe and will end up in delaying the project.
-
8.
Construction contractor inexperience of CRA, material leading to delay and rework High-pressure rating and corrosion resistance alloy (CRA) materials are not widely used in the company and the contractor may not be familiar in construction using this type of materials.
-
9.
Late arrival of materials on site due to poor vendor performance or quality failures The failure of vendor in delivering materials as per the agreed schedule and the quality thereby delaying construction activities and hence the overall on stream date.
-
10.
Late provision of vendor data resulting in a delay of the Approved for Construction (AFC) package Without vendor data, the engineering contractor cannot furnish the design leading in delay in delivering the AFC.
-
11.
Late placement of the purchase orders If there is delay in placing the purchase order (PO) this will result in delaying the startup of construction activities.
-
12.
Market price rise leading to an increase in CAPEX This is a global risk which will significantly affect the cost of all the items.
-
13.
Lack of Sour experience of E&P contractor leading to rework The design specifications for sour facilities are quite stringent compared to sweet service and were developed recently. So the engineering contractor may not be familiar with these specifications.
-
14.
Lack of adequate operations staff to support construction, commissioning and start-up There is no dedicated operation staff for this project and it is shared with other fields.
-
15.
Unauthorized deviation from vendor leading to rework or schedule delay Vendors have to design their equipment as per the project-developed philosophies and company design specifications.
-
16.
Construction productivity is poor due to concurrent operations and H
2
S safety measures This is similar to risk No. 1 with the difference that the delay due to this risk is solely driven by the safety measures and not by fatality occurrence.
Next, to rank and evaluate the identified risks, qualitative comparison was done using risk assessment matrix as shown in Table 4. The ranking ended up by defining risk as high-, medium- or low-level risk. This is achieved by understanding the impact of risk and then through the experiences of the project team of how likely that risk occur. The intersection of consequence and likelihood from Table 4 would define risk as high, medium and low. It should be noted that the 16 risks that have been identified involve consequences only to the people or assets.
Table 4 Risk assessment matrix
To use the result of risk assessment matrix for further analysis, it is necessary to convert qualitative description on risk into quantitative value, which will be an input to the simulation model. Such conversion, in the form of probability, is carried out by seeking expert opinion. These probabilities were used in building the stochastic model. Table 5 lists the risk factors with their consequences, likelihood, level of risks and associated probability. These numerical values for probabilities were collected from the project’s team engineers through a brainstorming discussion. The team consisted of two project engineers, one rotating equipment engineer and one planning engineer. For those risks where there was debate on their values, an average value was considered. These risks have been identified as possible sources of causing either project overrun or delays.
Table 5 Selected risk factors with their probabilities
Model construction
The model as displayed in Fig. 1 is constructed using software called RiskyProject Professional™ which is a project risk management tool provided by Intaver Institute. During model construction, the costs were broken down and assigned to activity levels, which were then defined by specific probability distribution. In addition, in the model, the probability and occurrence of risks were defined to activities and resources and then assigned by numerical values. Finally, the maximum and minimum durations on the activities were defined in the model, which were collected through brainstorming sessions with engineers from various discipline related to the project. The maximum and minimum values for the cost items were not available. Since the overall cost estimation is within −10 to 15% accuracy from historical data, the individual cost items were provided with the same range for fixed cost items too due to the market uncertainties. Also, the following assumptions were considered in constructing the model:
-
According to PMI standard (1996) triangular distribution is selected for activities and costs.
-
The calendar is based on 10 working hours per day and 5 working days per week.
-
The cost per man-hour was derived from the total cost estimate and the estimate of man-hour for detailed design.
-
Links between activities are maintained as per MS original Project plan. The most common link used to define relation between activities is Finish to Start (FS).
Each of the identified risk has been assigned to certain activity and/or resource, i.e., the impact of that risk can lead to delay of that assigned activity or increase of cost in the assigned resource or influence both. While entering the data in the risk register, the following assumptions have been considered:
-
The impact/probability of the same risk factor is not necessarily the same for activity and resource.
-
For a risk factor linked to a number of activities, probability has been broken down to the various activities as advised by the software support.
-
No correlations between risks have been considered.
-
Correlations between risks and schedule/cost have been considered by linking the risk impact to activities and cost items.
Running simulation
Model validation
The result obtained from the model is as shown in Table 6. This result was validated by crosschecking it with the results obtained from the qualitative analysis. In the table, risks are arranged according to their ranking. This ranking comes from the output of the simulation model associated with the risk. As shown in Table 6, it was found that all the risks which have been ranked as high-risk factors are already classified by the project team for being at high risk (except for the risk of late placement of PO). Late placement of PO was classified at medium risk level. However, at the time this assessment has been carried out, the probability of this risk occurring has increased significantly.
Table 6 Result obtained from the probabilistic model
In addition to this, the results were discussed and shared with the project team. The project engineers have highlighted that with respect to the project’s duration, they anticipate a delay of at least 1 year and cost overrun of not less than 10% over the total estimated cost.
Results and analysis
Project cost
The results from the model runs related to the costs are summarized in Table 7. The base cost provided in the company cost estimate (Table 3) is $99.7 million as compared to $102.79 million by taking into account the uncertainty in the cost item but without considering any risk factors. On the other hand, maximum cost with risk factors can be seen as $125.09 which is around 25% more than the company’s base cost.
Table 7 Cost comparison (all costs are in million $)
The total estimated cost for this project is $121.02 (Table 3) million with contingencies and all other factors. Based on Fig. 2 we can say that there is 8% chance that the cost will exceed the total estimated budget. Figure 3 presents the frequency distribution chart for cost with risk factors being incorporated. The expected project cost (mean) and standard deviation are $117.43 and $3.3 million, respectively. This shows that the increase in cost due to the risks leading to extended project duration is not accurately predicted.
Further, the model sensitivity analysis helps identify that the major risks impacting the project’s cost were limited to three factors, which are listed below with their ranking:
-
1.
Late placement of purchase orders (43.8%)
-
2.
Unauthorized deviation from vendor leading to re-work and schedule delay (28.2%).
-
3.
Late provision of vendor data resulting in a delay of the AFC package (27.9%).
For risks 1 and 2, the impact of their occurrence is very significant and will lead to a cost increase of about $ 10 million (associated with the re-work and schedule delay). For risk 3, the cost impact is not significant (about $1 million). However, the impact on schedule of this risk is huge (3 months’ delay in detailed design). The cost associated with this activity will vary depending on man-hours necessary to carry out the activity.
Concerning the other 13 risk factors, their impact is negligible compared to the identified major risks. A sensitivity analysis has also been carried out assuming that these three risks have been mitigated and closed. This has resulted in risk No. 5, i.e., complex interfaces between the different vendors, being the most critical risk with severe impact on cost.
Project duration
The results from the model runs related to the project duration are summarized in Table 8. The table summarizes the results of predicted on stream date and compares it with the base case scenario.
Table 8 Completion date scenarios
The base schedule without considering any risks and with the assumption that activity distribution is uniform is estimated to take total duration of 782 days and finish by 9th November 2013. Since the distribution of each activity has been defined as triangular distribution, with most likely, optimistic and pessimistic durations, the model has predicted the different scenarios of completion based on the defined distributions.
The promised on stream date to management is October 2013. However, as shown in Fig. 4, the model has predicted 0% chance that the project can be completed before April 2014 if we take risk factor into account. Figure 5 indicates that there is only 55% chance that the project will finish before Feb 03, 2015.
Similar to cost analysis, further, model sensitivity analysis helps identify major risks affecting the project’s duration, which are listed as below with their ranking:
-
1.
Unauthorized deviation from vendor leading to re-work and schedule delay (39.9%).
-
2.
Late provision of vendor data resulting in a delay of the AFC package (24.3%).
-
3.
Late arrival of materials on site due to poor vendor performance and quality failure (10.6%).
-
4.
Complex interfaces within package vendors (10.1%).
-
5.
Lack of installation and commissioning spares leading to delays (7.9%).
-
6.
Failure during acceptance tests (factory and site) resulting in delays (7.1%).
Risks 1, 2 and 4 are causing delay in detailed design activities. For example, risk 4 is the result of having number of vendors working in different interfaces. Historically, this risk has caused severe delays in past projects. Risks 3, 5 and 6 are related to construction and commissioning activities.
Concerning the other ten risk factors, their impact is negligible compared to the identified major risks. A sensitivity analysis has been carried out further assuming that these six risks have been mitigated and closed. It was found that failure of vendors to comply with approved designs (48.9%) is the most critical risk. This risk will have a severe impact on duration. This is followed by the late placement of PO (34.8%) and then by the lack of operation staff (16.3%).
The impact of increased cost and duration has also been checked on the Net Present Value of the project using economical spreadsheet. The incremental oil production introduced due to commencing of this project is expected to be in an average of 2500 barrels per day. The NPV calculation was performed for two cases. Case one with the original cost and target on stream date. Case two with results achieved from the high-risk run with a delay of more than 2 years and probability of increase in total cost by 8%. Operating cost has been ignored and same oil price, discount rate, and field life have been considered for both cases. The reduction in Net Present Value (NPV) with the increased cost and delayed on-stream date is estimated to be 72%.