field and office oil and gas technology

Upstream Business Process and Data Sharing

Author: Richard Brogan, Vice President Consulting, Products, 3esi-Enersight

Many upstream O&G companies face the challenge of managing and guiding their business with inconsistent and old data. This leads to inefficiencies, lack of insights and increased risk due to lack of information and alternatives.  The challenge is not new and companies are taking steps to improve the situation. In what follows, we consider this problem and outline an approach based on sharing data and models across business processes.  The key elements are:

  • Shared consistent “evergreen” data across all processes
  • Granularity suitable for the process in question
  • Aggregation as required but without loss of visibility, sometimes known as the “Golden Thread”
  • The ability to capture “Actuals” and compare with forecast data
  • Calculated data, such as fiscal data, on demand
  • The ability to archive and compare data

The Business Problem

Most upstream Oil and Gas companies face major challenges in obtaining accurate and consistent data for use in Strategic, Long Term Planning, Budgeting, Reserves Reconciliation and Reporting.  The data fits into three categories:

  1. Corporate data: FX Rates, Prices, Inflation indices etc. This data is generally consistent but there can be problems ensuring the latest set is used
  2. Measure data: Production, CAPEX, OPEX etc.
  3. Calculated data: Revenue, Tax, Free Cash Flow etc.

The major challenges are items 2 and 3 simply because in general, it is slightly easier to check the corporate data.

Additionally, differing processes require data at differing levels of granularity.  For example, Strategic Planning will often work with decision units that are aggregations of a number of projects.  Yearly granularity is common for Long-term planning while budgets are monthly.

Another common problem is the time required to gather the data compared to that available for analysis.  This often leads to adopted plans with very little scenario analysis having taken place.

Finally, there is the “glass walls” phenomenon where departments or individual do not share data.  This leads to confusion, inefficiency, and decisions taken using inaccurate information.

The above lead to it being common for the first item at meetings to be ensuring everyone has the same data, we have all been in meetings where person A has version 13 while person B has version 11.5!

Common Solutions

Companies recognize these issues and attempt to put processes and systems in place to negate the problems; however, at best these are normally only partially successful.  Consider some of the approaches used (companies may use combinations of these):

  1. Spreadsheets:

Each department generates a spreadsheet representing its data.  This data is aggregated across the business unit or at the corporate level to provide a snapshot of the business.

There are a number of recognizable issues with this approach:

  • Aligning the assumptions used across departments. We have all heard stories where the drilling team assumed 10 wells, production assumed 12 and facilities 5!
  • Little visibility into the assumptions used
  • Loss of visibility and ownership as the data is aggregated
  • Hard to update, track and compare
  • Time-consuming to compile
  • Calculated variables can only be generated once all the sheets have been combined/aggregated

2. Template Spreadsheets: 

This approach is a refinement of the individual spreadsheets where a defined template spreadsheet attempts to contain all the data needed for planning, reserve consolidation and reporting at a specified hierarchy unit in the organization such as a business unit.  Completed within a given schedule the sheets are held in a specified folder.  The bespoke software accesses the folder to read the sheets into planning or reserves systems.

This approach partially addresses the problem of sharing common data; however, there are a number of problems:

  • The departments generating the data and adding to the sheets often regard this as an activity that generates very little benefit for the department
  • It is time consuming and hard to amend the template
  • Difficult to compare and identify changes in the data during planning cycles
  • Updated at fixed points in time, normally only a few times during the planning cycle. This results in not being able to easily answer questions related to the latest situation
  • Normally only contains data at one level of granularity
  • If the template contains calculated data related to Fiscal measures such as free cash flow then this fixes the value of the data to that set of corporate data assumptions. Different scenarios require new folders and new sets of templates to be created.

3. Data Cubes

This approach provides a store for pre-calculated data and shares data via a Business Intelligence systems reports.  It is primarily a reporting tool. This provides a partial solution, the challenges with data cubes are:

  • The data is all pre-calculated and is designed for good performance when retrieving data. Due to the amount of data, the cube is normally built overnight and so provides access to the previous day’s data.
  • The non-dynamic nature of data cubes means it is not possible to have available the latest data, under normal circumstances this may be acceptable but towards the end of a planning cycle there are a large number of last minute changes
  • The cube is not well suited to aggregating data, differentiating between gross and net, rolling up data through hierarchies etc.

4. Commercial Tools:

A wide range of commercial tools are available, from different companies, to address specific business processes such as Asset Planning, Capital Management etc.  These tools offer good point solutions but are not designed to share data with other tools.  Where companies have acquired a number of these tools, the initial effort to pass data between them, via bespoke links, is large and changes/updates to the software can involve significant work to maintain the links.

Ultimate Best Practice

In an ideal world, to achieve the most accurate and consistent data, upstream oil and gas companies need:

  • Shared consistent “evergreen” data across all processes
  • Granularity suitable for the process in question
  • Aggregation as required but without loss of visibility, sometimes known as the “Golden Thread”
  • The ability to capture “Actuals” and compare with forecast data
  • Calculated data, such as fiscal data, on demand
  • The ability to archive and compare data

Few (if any)  organizations consistently achieve all the above, although a number are working towards this utopia.

The diagram below illustrates a number of key business processes and the interaction between them.

Integrated Workflows for Oil and Gas Corporate Strategy, Long-Term Business Planning, Asset Developmemt, Capital Management, Corporate and Technical Reserves

The key elements of this are:

  • A common evergreen inventory of existing projects and new opportunities. This is used by all the processes to ensure consistent data
  • A common set of corporate data such as FX, Prices etc.
  • A common set of on-demand economic/fiscal models
  • Historical data and forecast data is captured in the system

Comments on the interactions between processes:

  • The strategic planning process extracts all existing projects and opportunities from the inventory, aggregates into decision units whose size will depend on the size, risks, and dependencies of the projects/opportunities. Portfolio optimization and scenario analysis are conducted to gain insights into the data and the feasibility of meeting the corporate strategic goals. Guidelines are produced for the business units in terms of targets, constraints, and project mix that are required to meet the corporate goals.
  • Long-term business planning is conducted using the corporate guidelines. The granularity of the opportunities and existing projects will vary depending on their maturity.  The first year of the long-term plan is the budget, and this will normally be at a monthly level of granularity. Projects and opportunities are flagged to indicated submission into the current long-term plan.
  • Asset development planning provides a detailed analysis of an existing field or an opportunity. This provides detailed data into the inventory at a fine granularity. The business planning system may not use this level of granularity but can aggregate the data.  The key aspect is that there is a “Golden Thread” of data to allow visibility at each level as to the source of the data.
  • Capital management is the control of spending that has been approved and the reforecasting of spend for existing projects. It will take and add data to the inventory for existing projects.
  • Technical evaluation of reserves extracts data from the inventory for existing projects to update the forecasts. Updated forecasts are placed into the inventory.
  • Corporate Reserves has all the data required within the inventory for reporting and consolidation. The inventory contains production, updated forecasts, plans for new opportunities, etc.  It will also have the data to undertake reserve forecasting.
  • The above interactions are often iterative and archives are kept for each iteration to allow comparisons to be made and changes tracked.

Enlightened Upstream O&G companies are starting to implement the above using innovative processes and tools to assist in this exercise. 3esi-Enersight is proud to be the leading provider of integrated Strategy, Planning, and Reserves, helping operators minimize inefficiencies and risk from lack of information, and improve company-wide insights. Integrated upstream planning using a process like the one above is helping operators in 2017-2018 create tangible opportunities for sustainability and growth. We invite you to contact us to learn more.

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