Drilling additional wells in productive acreage is common practice. Determining optimal placement to maximize production for new wells and anticipating the impact on existing wells is a challenge. Overly cautious or excessively tight spacing can decrease well productivity, making the negative impact on ROI too much of a risk.
When the VP of engineering for a mid-size oil company had wells being drilled in close proximity to existing wellbores the production team noted a significant impact on current production when each new well came online.
Using the Well Spacing Optimization Workflow in DI Transform, the production team was able to quantify the impact of new wells on existing production and determine optimal well placement to maximize productivity in both new and existing wells.
ANALYZE WELL SPACING
In order to predict the impact of future drilling activity in crowded acreage, the team first needed a detailed understanding of how recent infill wells had affected overall productivity.
Using DI Transform, the team could quickly calculate lateral distances to nearby wells at the time they were drilled – using this information as part of a sophisticated multivariate model incorporating relevant production, engineering, geoscience, and seismic data. Within minutes the team generated variable plots that made it easy to identify important trends and gauge variables like:
- Wellbore separation distance
- Well age & production history
- Engineering details such as proppant per foot and the extent of subsurface fracturing
- Geological characteristic such as rock properties and fault location
Companies that attempt to study the impact of newer wells on existing production tend to be limited to review of basic factors. Building more sophisticated multivariate models could take months, and the models would still exclude crucial elements such as reservoir quality.
CREATE A SWEET SPOT MAP
The team needed to apply their model to the company’s open acreage to identify promising new well sites and assess their potential productivity.
Using the multivariate model within DI Transform, the team created a series of graphs to enable rapid, visual analysis of key factors. This analysis indicated that new infill wells maximized production when they were drilled at least 2250 feet from existing wells that were both high-producing and had been producing for less than 200 days.
Without intuitive heat maps based on robust multivariate analytical models, narrowing the options for new infill well sites is hit-or-miss. Comparing potential sites is an even less precise process, and the cumbersome analysis involved creates a high likelihood of inaccurate results or an incomplete basis for decision-making.
ASSESS IMPACT ON EXISTING WELLS
To make sure that new infill wells wouldn’t drain production from current wells the team needed to assess the new wells’ impact on existing production.
To conduct an interference analysis examining the impact on existing wells, the team took advantage of DI Transform’s Producing Days Tool. They looked at existing wells’ production before and after the addition of proposed new infill wells and analyzed changes in water cut for existing wells.
Companies might consider the “big picture” and weigh the impact on existing production, but would likely be forced to use a limited set of variables to build crude models. This painstaking process could yield questionable results, and the opportunity cost of postponing drilling while chasing answers would also reduce ROI.
OPTIMIZE TOTAL PRODUCTION
The final step was to compare predicted production of new wells to the impact on existing production, so the VP of Engineering could recommend the optimal placement for maximum overall ROI.
With DI Transform, the team was able to review them side-by-side and identify the most promising places to drill to either maximize new production or boost existing production.
Without the advanced functionality and intuitive tools in DI Transform, companies would struggle to conduct this kind of analysis at all. In most cases, recommendations would have to be based on predicted productivity of new wells alone, resulting in millions of dollars of unrealized profit.
The VP of Engineering selected two sites for new infill wells. Once the new wells came online, both began producing at or above the volumes expected. The existing well saw an immediate increase as well. Within the first three months, production aligned with the volumes predicted by the DI Transform model with exceptional accuracy, validating the team’s analysis and resulting in a major boost to revenue.
Based on this success, company leadership decided to increase investment in infill drilling, confident that the VP and his team would be able to pinpoint additional well sites to maximize productivity across their portfolio and drive ROI through the roof.
Learn how Drillinginfo’s solutions can help optimize well placement for maximum production and ROI from new and existing wells. Speak with a dedicated DI Transform specialist today.