Selected Projects

WellView Well Lifecycle Application Upgrade, Integration, Migration & Implementation

WellView (Peloton) is the industry-standard platform used to manage and report on the full well lifecycle, from planning and drilling through to completion, testing and workovers. At Origin, it serves as a business-critical Integrated Gas system and the source of truth for thousands of wells.

I led the business and technical stream for the upgrade and migration from Origin’s internally managed, AWS-hosted WellView 10.4 environment to Peloton’s SaaS-based WellView Allez platform. Working across both technical and business streams, I ensured requirements, integration impacts and operational dependencies were clearly identified and prioritised. This included coordinating user remediation and delivering on-site training to well engineers at remote drilling locations, as well as office-based teams.

Given the breadth of downstream dependencies, a key focus of my role was assessing and managing the repointing of integrations and reporting layers to the new platform. WellView interfaced with multiple enterprise and specialist systems, including SLB’s OFM, Origin’s Snowflake Integrated Data Hub, Profisee Master Data Management, ArcGIS applications, Ataccama data quality platforms, multiple in-house databases and an extensive Power BI reporting estate using both data flows and direct connections.

Using technologies such as Dell Boomi, SQL Server Integration Services and internally developed APIs, I identified critical technical and business dependencies, worked closely with stakeholders and SMEs to prioritise high-impact integrations, and supported structured testing and transition activities. The objective throughout was to maintain operational continuity while modernising the platform in a controlled, commercially aware manner.

WIMS (Well Integrity Management System) Tech Analysis, Procurement, Integration & Implementation

As part of the Well Integrity Management System (WIMS) Program, I conducted a deep-dive current-state assessment of how Well Integrity is governed, assessed and operationalised across the full Well Lifecycle — from drilling and handover through to operation, suspension and abandonment. This work focused on how responsibility transfers between Asset Services and Assets via the Well Handover process, and how Production Engineers, Well Integrity Engineers and the Technical Authority rely on WIMS as the system of record for integrity status, risk classification and regulatory evidence.

Through workshops and structured interviews across Asset Services, Production Engineering, Field Technicians and Technical Authority teams, I mapped how WIMS is expected to support the “traffic light” risk model defined in the organisation Well Lifecycle Integrity Management Plan. This model governs prioritisation of well failures, where higher-risk barrier failures override lower-risk conditions (via a traffic light system). I identified that the current WIMS implementation does not support automation of this model and instead relies on manual status updates — a method widely regarded by engineers as unsustainable, error-prone and unsuitable for managing thousands of wells at Origin.

While initial assumptions pointed to technical limitations of the existing WIMS platform, my analysis demonstrated that the issues were systemic rather than purely technological. These included a lack of fit-for-purpose configuration, absence of defined data governance and workflow standards, minimal training since system adoption, and no clear business ownership or system champion. Engineers openly expressed low confidence in WIMS data, resulting in critical integrity analysis being performed outside the system using spreadsheets, email and SharePoint — with WIMS acting largely as a passive reporting tool after the fact.

A significant focus of my work was documenting how Well Integrity Assessments and Fitness-For-Service evaluations are currently performed. These assessments rely on highly manual Excel-based workflows, pulling data from multiple external systems and field data loggers, often via screenshots or email requests. Calculations, interpretations and approvals are performed offline, then manually uploaded into WIMS, emailed to stakeholders and submitted to the regulator where required. Revisions require repeated manual cycles, creating duplication, audit risk and latency in regulatory response.

I identified that the lack of end-to-end automation, role-based controls and system-driven workflows introduces material risk. Status changes can be made without appropriate verification, barrier element failures cannot be traced historically, time-to-failure metrics cannot be calculated, and leading indicators of integrity degradation are not surfaced in real time. Integration gaps with systems such as MDM (Master Data), SAP, Nexus and OCIS (Risk Management) further exacerbate these risks, with action tracking, ORAs and compliance deadlines frequently managed outside WIMS.

This work culminated in a clearly articulated problem statement: WIMS, in its current form, does not provide the level of assurance required for a safety-critical, regulator-visible system. The findings reframed the programme from a software upgrade into an enterprise integrity management transformation, with emphasis on automation of the traffic-light risk model, system-driven workflows, data lineage, auditability, role-based governance and integrated regulatory reporting.

I translated these findings into a structured set of business and regulatory requirements covering action management and workflows, integrity reporting, failure management, maintenance results, fitness-for-service assessments, action tracking and advanced analytics. These requirements formed the foundation for evaluating replacement, re-platforming or internally developed solutions capable of supporting proactive integrity management, predictive analysis and scalable compliance as Origin’s well portfolio continues to grow.

Oracle eAMS Asset Management Migration                                                     

Following ConocoPhillips’ near-acquisition of Origin’s APLNG interests, a decision was made to segregate and migrate APLNG Asset Management data from Oracle e-Business Suite (eAMS) to an alternative platform. I was engaged to assess viable migration strategies for more than 3TB of asset data and millions of associated attachments, with a focus on long-term sustainability, cost control, delivery risk, and operational continuity.

I led the business and technical assessment, covering requirements definition, risk analysis, vendor engagement, and cross-functional workshops. Drawing on extensive hands-on data migration experience, I was able to accelerate the analysis while ensuring technical complexity and downstream dependencies were fully understood. A key part of the role involved bridging business stakeholders, architects, DBAs, and developers — aligning commercial objectives with delivery reality and prioritising options that were both achievable and cost-effective.

The recommended options included migration to SAP Asset Management (already implemented elsewhere within Origin under a separate hierarchy) and consolidation into Origin’s Snowflake-based Integrated Data Hub, with AWS used for attachment storage.

During the assessment, I identified an opportunity to migrate more than three million attachments — work previously deemed too complex by two separate teams. However, I recommended, designed and implemented a practical solution to extract and migrate these files into Amazon S3, ensuring they were searchable and accessible. The related asset data was structured in Snowflake and surfaced through a Power BI dashboard that I developed, delivering a usable, integrated outcome rather than a simple data transfer.

Well Analogues to determine Anomalies, using Artificial Intelligence

I worked alongside Data Scientists and Production Engineers to help shape a proof-of-concept aimed at improving well intervention decision-making through machine learning. The initiative addressed a longstanding gap within Origin: the absence of a systematic method to compare wells across thousands of assets and apply learnings from historical performance to current operational decisions.

The business case centred on well impairment and workover selection. Between 2020 and 2024, over 1,900 major workovers were undertaken, with approximately 58% resulting in impaired recovery. This translated to an estimated production impact of ~100 GJ/day per affected well and a potential financial exposure of up to $50 million per annum. My role involved articulating this problem in commercial and operational terms, translating data science concepts into a business-aligned initiative with measurable value.

Working closely with SMEs, I supported the development of a similarity-based model that compared wells using engineered attributes and performance history, enabling engineers to identify the most relevant historical analogues for a given well at a point in time. The objective was not automation for its own sake, but improving confidence in high-cost decisions such as Live Workovers — which require specialist equipment, incur mobilisation costs, and carry material production risk.

I led interviews to refine impairment definitions, clarify similarity criteria, and define success metrics for a phased deployment. I also structured the proposed roadmap covering model validation, data integration (via the company Data Warehouse and Databricks), governance, and potential downstream integration with Well Intervention Tooling. The initiative was positioned as a decision-support capability designed to complement engineering judgement rather than replace it.

The outcome was a validated proof-of-concept, executive-ready business case, and structured project pathway that positioned the initiative for controlled production deployment. Beyond impairment, the model framework was designed to support broader use cases including pump failure analysis, turndown recovery, and future well design optimisation.

Schlumberger IaaS Alternative Evaluation                                        

Origin’s Integrated Gas Business Unit relies on a broad suite of subsurface modelling and reservoir engineering applications, including SLB’s Petrel, OFM, Eclipse, Intersect and GeoLog. These systems underpin critical reservoir modelling, forecasting and geotechnical analysis activities and were hosted on SLB’s Infrastructure-as-a-Service environment, BluCube.

With BluCube approaching end-of-support, I was engaged to assess and recommend a sustainable replacement strategy for the infrastructure supporting Origin’s entire subsurface application landscape. The options considered ranged from vendor-led managed services through to cloud-native, on-premises and hybrid models, including both SLB and competitor offerings.

I led a structured evaluation process, narrowing the field to SLB’s DELFI Platform-as-a-Service, Cegal’s Cetegra, and GeoComputing’s RiVA. Assessment criteria extended beyond technical capability to include performance benchmarking, implementation complexity, cost modelling (from transition through ongoing subscription), delivery timeframes, scalability and long-term support viability.

The objective was not simply infrastructure replacement, but ensuring continuity of critical subsurface workflows while positioning the business for flexibility, cost control and future expansion.