Loss of containment (LOC) issues are every oil and gas operator's nightmare. These low frequency, high consequence spill-events have the potential to adversely affect the environment, an operator's financial health and public perception. For operators with mature aging assets and a sizeable well count, the probability of a LOC event is more likely. As the industry moves towards increased efficiency, there is a growing need to get more well integrity projects completed despite competition from oil-generating projects in the company-portfolio. This has necessitated re-thinking our response to the fundamental question of "how can we work within the existing constraints to ensure a robust well integrity program that protects people, the assets and the environment from a LOC event?" We show in this paper, a risk-based approach to solving this challenge. With over 1000 well strings, the starting point was having a comprehensive well integrity management system underpinned by a robust database that contained the test records of all well-related safety devices. A swiss-cheese model was then applied to analyze each device (Downhole safety valve, Wellhead valves and Casing valves) as a layer of protection considering possible hydrocarbon flow-paths. With this new methodology, each safety device was assigned a risk-factor denoting its relative importance in preventing the occurrence of a LOC event. Multiple safety device failures (e.g. combined failure of downhole and wellhead valves) had extra penalty assigned since holes lining up in the swiss-cheese would allow a catastrophic event pass through undetected. The risk factors were then summed up for each well to generate a risk-index that was used to compare wells and prioritize barge intervention activities accordingly. The key message is that catastrophic events typically require multiple safeguard failures and we can significantly reduce the chances of its occurrence by applying a risk-ranked approach to well integrity.

Mature fields typically require a considerable amount of attention and manpower to keep their production going. Typical daily operational challenges include identifying wells that quit, reactivating such wells and gathering wellhead/casing pressure data that are used for well integrity, surveillance and optimization studies. These challenges are further compounded for mature assets that have a significant number of wells spread across wide geographical areas, leading to a never-ending cycle of data gathering while reactively chasing wells that have quit to minimize lost-production opportunities (LPO). One way to manage these challenges is to install sensors that leverage on the Industrial Internet of Things (IIoT) on wells to achieve remote well monitoring. The sensors are used to monitor critical well parameters (pressures, temperatures) remotely, thereby reducing Opex incurred via helicopter trips to diagnose well problems. The solution was also configured to report shut-in wells via email/texts helping to narrow down the culprit well, reduce reaction time and minimize LPO. More value can be derived beyond gathering surveillance data and reducing LPO reaction time. The data can be delivered real-time to the Asset Engineers in the office to drive engineering analysis on wells. Such analysis could lead to proactive solutions such as optimizing wells that are already on gas-lift or quicker decision-making to initiate gas-lift on a well just before it quits. In this paper we demonstrate the value that was created by implementing remote well monitoring in mature fields using case-studies that capture the daily field operational challenges and how they were resolved leading to significant cost savings.

The use of cement packers to access behind-pipe hydrocarbon opportunities has opened up significant reserves without the attendant cost of a rig. A key challenge with this technique is the attendant high skin that results from the cement packer which significantly impacts initial production rates and recoverable reserves. The objective of this paper is to share technique and lessons from a case study in a mature field, offshore Niger Delta where an innovative technique was employed to place the cement packer above the perforation interval in the target reservoir. This eliminated the skin due to the cement packer, leading to significantly higher initial production rates when compared to analog workovers. The paper details operational procedure during execution. The lack of a local precedent in the deployment of this type of cement packer presented a key challenge. Perforating the target reservoir and string without impacting the second string in the wellbore was another challenge. The initial production rate from the case study was 2200 BOPD vs 800 BOPD or less from analog cement packer workovers. A key lesson learned is that this solution is best suited to wellbores with a single production string only or multiple strings wellbores in which there is no further production utility for the additional strings. The follow on best practice from this lesson is to fully evaluate the wellbore utility for any identified opportunity of this sort to ensure the deployment of this method does not impede the utility of the wellbore for future reservoir management operations.

This paper reviews a history matching case study of a reservoir with two oil producers located proximally in the same reservoir, with a slight vertical offset. This proved challenging to match due to the significant difference in the water production trends. This study highlights the methodology taken during the history matching process to identify the key element(s) responsible for the marked difference in water cut trends. The objective of this paper is to share steps taken in identifying the variables responsible for the observed behavior and showcase the results of key tests on variables in the reservoir during the history matching process. Details of the investigative process undertaken to identify the defining variable/element impacting the water production performance will be shared with lessons learned from the process itemized. The history match efforts revealed that the difference in water production signatures seen from both wells close to each other was because of the contrast in reservoir static properties which occur between the wells. This prompted a revisit of the seismic data for the region, which corroborated the updated reservoir understanding. Following these learnings, the history match project was completed and resulted in the optimal placement of a new development producer well. Initial production results from the new development well matches closely to the model forecasts, further validating the model parameters and stratigraphic inferences. A key lesson learned from this project is that localized history matching difficulty is best tackled by first reviewing drilling and completion data for the area of interest, the initial test data and a revisit of the stratigraphic concept use in the earth modelling phase of the project. As a best practice, thorough investigation of stratigraphic concepts for the reservoir alongside analog reservoirs will help in a more accurate first-time description for the reservoir.