Genuine Value

At Xtega we work to add genuine value to our client organisations through seamless collaboration with internal and external resources, continually striving to achieve new levels of technical innovation, and by maintaining absolute standards of professionalism and excellence in all activities undertaken.

Effective and Productive

The services and products provided by Xtega have a specialist focus. A technical edge is maintained through an ongoing R&D program, an active PD program, and an ongoing focus on broader industry developments.

As such Xtega specialises in working effectively and productively within the teams in which we are placed.

Qualified Network

We also have a network of highly qualified colleagues from a wide range of disciplines that we can call upon to complement teams as the client may require.

Xtega Pty Ltd was established in 2012, and is based in Brisbane, Australia.

Strategic Planning

Xtega has a proven track record of providing strategic planning services to the mining industry.

Professional services provided range from brainstorming and mind mapping of options, through to detailed strategic optimisation models using the latest cutting edge software and optimisation algorithms for individual mines through to entire country and commodity business units.

Such analyses have been conducted using a range commercially available software solutions, at times supplemented with customised software and modelling solutions. Refer to the Software Solutions section for a range of software packages used by Xtega.

Our core strategic planning services include:

Ultimate pit selection

Cut-off grade optimisation

Grade-throughput-recovery optimisation

Schedule optimisation

Pit sequence optimisation

Throughput optimisation

Capital sizing optimisation

Strategic scenario selection

Advanced Valuation

Relationships exist between costs and prices in almost all mining valuations (e.g.: between the copper price and the diesel price). Not including these relationships will result in inaccuracies in the valuation model. This can then lead to suboptimal decisions relating to investments or future strategy.

It is especially important to incorporate these relationships any time the absolute valuation outcome is important, or significant capital is to be invested.

The Correlated Valuation Methodology (CVM) has been developed by Xtega and can be used to:

  • Analyse and model the key relationships.
  • Improve the accuracy of the valuation outcomes.
  • Calculate and assess the internal cashflow probability.
  • Model and assess the residual uncertainty.
  • Make confident investment decisions based on superior strategic analyses.

Xtega has developed a number of proprietary tools and methodologies to quantifiably improve the valuation accuracy of almost any mining asset. These methodologies are underpinned by sound financial theory, as well as a statistical and mathematical basis the process for which can be clearly explained.

Xtega has filed provisional patent applications for a range of the valuation approaches and techniques developed.

Read more about:

Relationships can be seen to exist between parameters in mining valuations, consider the following graphs.

These relationships have all been analysed by Xtega, and all of these are statistically significant. As such each of these parameter pairs can be seen to be correlated, meaning that the two variables move in relation to each other. Note that this does not imply causality.

If these correlations are not considered, the resulting valuations will have an unquantified error. The CVM covers this and more.

The purpose of the CVM is to:

  • Increase the valuation model accuracy.
  • Recognise and incorporate the relationships between parameters.
  • Reduce and quantify the risk resulting from systemic market forces.
  • Reduce the variation in the residual uncertainty.
  • Therefore increase the overall confidence in the valuation outcomes.

The concept has a pragmatic framework which selects a central parameter (e.g.: for a copper mine this would typically be the copper price), and then seeks to assess and model the correlations between the remaining key correlated parameters (typically including diesel, steel based consumables, labour, power, tyres, explosives, chemicals, etc., etc.).

Whilst sections of the CVM analysis are complicated, the concept overview and the presentation of the outcomes are designed to be simple to interpret and easy to understand.

Download a white paper on the Xtega CVM process

Download a case study example of the Xtega CVM process

Download a time-step case study on the Xtega CVM process

Download the Xtega CVM technical paper

To access a range of complimentary CVM reports and CVM predictive equations please visit the Products section.

An overview of the main tasks required to be completed when incorporating the CVM into a valuation model includes the following.

  1. Select a central parameter. This would typically be the main revenue driver, i.e. for a copper mine this would be the copper price.
  2. Assess and analyse the historical relationships between the central parameter and each of the other relevant input parameters.
  3. Where correlations are identified, develop a regression analysis equation including the central parameter as a variable in the equation.
  4. Utilise a combination of the predictive time series for the central parameter (typically sourced from the corporate assumptions) and the CVM equations developed to generate the cashflow statement.
  5. Measure the resulting internal probability of the cashflow.
  6. Simulate and assess the residual uncertainty.

Once the CVM has been incorporated in the financial valuation framework it becomes possible to calculate the internal cashflow probability (ICP) of both the preceding valuation and the CVM valuation. The ICP is a measure of the risk consequent from systemic market forces. This risk is considered to be comprised primarily of variations in the expected outcomes from the correlated parameters.

Resultant CVM internal cashflow probabilities are typically +P80, whereas standard models which do not incorporate the correlations between parameters are often sub-P50. Thus the accuracy of an otherwise high quality financial model can be significantly lower if the relationships between key parameters are not recognised and modelled.

Subsequent to calculating the internal cashflow probability it is then possible to calculate a value at risk (VaR) as a measure of the value of the resultant risk based exposure to systemic market forces.

Almost all projects and operations have the main revenue price assumption (the central parameter) as the parameter to which the value is the most sensitive.

If the uncertainty in this variable is modelled stochastically inclusive of the CVM the resultant distribution changes. Consider the following two graphs.

Note that the second distribution which is inclusive of the CVM has a narrower distribution and a reduced range. The range has been reduced from –US$806M – US$4,299M in the first graph (excluding the CVM), to –US$89M – US$3,645M for the second graph (inclusive of the CVM). Subsequent to including the CVM this project could say with a level of confidence based on sound analyses that it should not expect to lose circa a billion dollars.

The inclusion of the CVM in the project valuation has resulted in the uncertainty based variance being reduced by 19%, and the standard deviation by 10%.

The coefficient of uncertainty (coefficient of variation) has been reduced from 0.52 to 0.38, a reduction of 27%, and therefore a significant improvement.

The final valuation outcome, inclusive of the uncertainty caused by market volatility, is now more constrained. An intuitive outcome which allows greater confidence in investment decisions.

Engineering Services

Xtega provides a significant range of mining engineering services.

Whilst having an established reputation in delivering on a range of core services, Xtega also specialises in non-standard and more complex assignments. These have often involved assignments covering the review of multiple disciplines at a range of levels.

As an example such assignments have involved product reconciliation from block model, through mine design, mining operations, plant operations and transport to point of sale, and reviewing the processes of the EOM reconciliation processes.

Our core engineering services include:

Technical reviews and audits

Production performance reviews and improvement projects

Mine cost modelling and cost model development for budgets and LOM/LOA planning

Haulage simulation, modelling, and system calibration

Project management

Management support or infill roles

Performance improvement programs (operational and technical)

Capital expenditure justifications

Valuation of options

LOM/LOA scheduling

Operational reporting system review, development or upgrades

Mining engineering for scoping studies, prefeasibility studies, feasibility studies

Workshop facilitation

Xtega is also able to compile multi-disciplinary teams from our pool of associates and colleagues.

3rd Party Software

Xtega remains an independent consultancy, and as such selects the software and methodology most appropriate to the individual client requirements.

Software packages used by Xtega include the following:

Our Clients

Xtega has an ever expanding range of clients including:


Jensen & Curtis Global

Roc-Drill Pty Ltd


BHP Billiton

Laserbond Limited

Ok Tedi Mining Limited


Xstrata Zinc

Our Recent Projects

Xtega has completed a wide array of projects aross a range of commodities including coal and metalliferous operations and projects. Projects have ranged from production performance improvement through to financial analysis and strategic planning.

Feasibility Study Strategic Planning

Feasibility Study Strategic Planning (collaborative project).

Dragline Performance Data Analysis

Analysis of key performance trends in dragline KPI datasets.

Master Database Upgrade

Scaled upgrade of production reporting database and interfaces including development of customised code to suit the client business requirements.

Budget Planning Support

Driver Tree Development and Scenario Analysis

Dragline Performance Data Statistical Analysis

Analysis of dragline KPI data and analysis of statistical significance in production performance across time periods.

Colliery Margin Analysis

Numerous margin analysis studies have been completed by Xtega utilising a range of software packages depending on client systems and requirements. Static optimisation studies have included:

  • Lowest seam.
  • Primary wash density optimisation.
  • Coal allocation optimisation.
  • Maximum margin assessment.
  • Maximum value assessment.
  • Operating cost sensitivity.
  • Pit sequencing studies.
  • Capital allocation and sequencing.
  • Stockpile assessment projects.

Complex (multiple collieries and wash plants) Margin Analysis

"Margin analysis studies completed on multiple collieries and multiple wash plants with a range of possible coal destinations. Static optimisation studies have included:

  • Lowest seam.
  • Primary wash density optimisation.
  • Coal allocation optimisation.
  • Maximum margin assessment.
  • Maximum value assessment.
  • Operating cost sensitivity.
  • Pit sequencing studies.
  • Capital allocation and sequencing.
  • Stockpile assessment projects.

Coal Source-Destination Optimisation Study

Specific project to assess options for coal destination by individual coal parcel. Each coal parcel had multiple potential destinations for both the primary and secondary products, with a range of yields for primary and secondary product by primary wash density.

Independent Coal Recovery Review Project

"Review of technical and operational performance to identify sources of coal losses. Present the results to executive level management including an assessment of the budget and planning parameters used."

Coal Tonnage Flow Analysis

Identify and quantify coal losses from geological modelling to ex-pit weightometer including all technical and operational influences.

Performance Improvement Project (integrated technical + operations)

Integrate multiple departments to commit and deliver on a performance improvement project based on stated goals from senior management.

Included MindMapping workshops, subsequent resource based scheduling, and project management to delivery.

Strategic Planning Project: region based margin analysis + static quality-destination optimisation

Margin analysis for entire commodity division. Static optimisation studies included:

  • Lowest seam.
  • Primary wash density optimisation.
  • Coal allocation optimisation.
  • Maximum margin assessment.
  • Maximum value assessment.
  • Operating cost sensitivity.
  • Pit sequencing study.
  • Capital inclusion sensitivity analysis.
  • Stockpile assessment projects.

Production Report Model Development

Development of a production reporting system including customised code development as per the client requirements.

Independent Field Trials: data collection, analysis and reporting

Conducted independant field trials to support board level investment decisions. Project included:

  • Independent data capture and review.
  • Detailed data analysis and statistical analyses to provide appropriate confidence of a statistically significant difference in results.
  • Report development to support an ASX release.

Strategic Planning and Budget Planning Support

Strategic Planning and Budget Planning Support (collaborative project).

Strategic Planning Project: for region and complex

Included development and optimisation of both static and dynamic models, including multiple constraints and multiple quality and contractual based penalties.

Strategic Planning Project

Complex metalliferous project including multiple downstream process options.

External Gold Recovery Review

A board commissioned review relating to a disparity between budgeted and delivered gold production (collaborative project).

Strategic Workforce Planning

Business analysis and diagnostic to support development of labour model (collaborative project).

Labour and Overtime Model Development

General Consulting Support Project

Dragline analysis and driver tree model development.

Project to present dragline KPI and financial impact data as a dynamic and interactive driver tree.

Drill Performance Modelling

Production Database Review

Review of complex in-house database including development of user friendly tools to access data.

Driver Tree and Productivity Model Development

Project to present KPI and financial impact data as a dynamic and interactive driver tree.

Short-term Planning System Review

Review of the software systems, architecture, and interaction with adjacent systems and disciplines for a metalliferous mining operation.

Technical Services Support

Technical services support provided to a metalliferous mining operation.

Mine Operations Support

Mine operations support provided to a metalliferous mining operation.