Three keys to unlocking value in your exploration data
by NICK BURCHELL | November 4, 2013
According to a 2013 global survey report released by Geosoft, managing exploration data is now of critical importance for 44% of respondents, up from 18% two years ago.
Given the huge amount of data being collected, created and stored in historical archives, the scale of today’s big data management challenge can be daunting for exploration organizations to tackle. The ability to find data through integrated search tools, complicated data management workflows, data duplication and dependency on knowledge experts remain the biggest obstacles, according to survey respondents.
On the positive side, for those that are able to master their data challenges, there is tremendous, untapped value in having exploration information assets that are more usable, accessible and visible for decision making.
One of the questions many organizations struggle with is 'where to start' with data management?
Geosoft has worked with organizations of all sizes to define and address their largest exploration data problems, with goals targeted to achieving both immediate and long term value. Our data services team often engages in the early stages to scope out project requirements, review and address data issues preventing effective exploration of the data, and assess technology needs for search and discovery.
We’ve identified 3 key drivers that can be your first step towards improved exploration data management.
1. Optimized data quality, workflows and systems
Spend more time on data interpretation and knowledge development and less time on data handling and data management issues. Deliver accurate and relevant data direct to your interpretation platform of choice in the format of choice.
How? Routing out bad and/or duplicate data, inefficient workflows, and establishing a consistent, sustainable system for cleansing and publishing data, eliminates inefficiencies, and frees geoscientists to focus on opportunity and project development. As a general rule only 20-30% of exploration data is actually good, useful data. Up to 40% of bad/duplicate data can be resolved and/or removed through automation.
2. Improved data discovery and exploration
Rapidly find, integrate and draw insight from multiple data sources to accelerate and improve the quality of interpretations for better understanding, informed decisions and improved discovery success.
How? Implementing a standard system for publishing, distributing and discovering your exploration data ensures historical and new data are always available to be explored and exploited to their fullest potential. The ultimate goal is to make useful data instantly accessible and easily shared for improved, collaborative exploration decision making.
3. Increased visibility and transparency
Identify, catalog and securely store your data and information for future reference and audit. Increase the visibility and transparency of your exploration data to support regulatory, corporate and shareholder reporting.
How? Establishing necessary data standards and controls, and consolidating your multiple data sources within a secure, central environment ensures your exploration data repository can be managed and fully leveraged as an organizational asset. Visible, accurate, auditable data is the foundation for building corporate and shareholder value through your data asset.
Understanding the key drivers for improving information management within your organization - those that will deliver the greatest value – can be the starting point for addressing your data challenges.
Begin with a clear view of the problems you need to solve and what success looks like. This will help establish corporate commitment and resource allocation to keep data management projects on track and deliver impactful results.