Search Results for:

04 Jan 2018

Identifying Pipeline Leaks Quickly is Key to Minimising Risk

When it comes to today’s vast and complex oil pipeline systems, even the smallest leak can lead to extensive financial loss and lasting reputation damage.

The recent rare unplanned shutdown of the Forties pipeline in the North Sea, which supplies 450,000 barrels per day of crude to Britain, along with a third of the UK’s total offshore natural gas output, was caused by a crack found in the pipeline. The nearly month-long shutdown resulted in major refinery capacity shutdown, force majeure being declared and oil and gas prices reaching their highest points in years. Additionally, the owner of the pipeline has faced harsh criticism for its handling of the situation.

Internal pipeline leak detection systems are commonly used to detect a leak. These systems use point sensors to track flow rates, as well as apply mathematical and statistical computations to monitor flow rates, pressures, temperatures and product characteristics. Although these systems are useful in identifying leaks, they lack in sensitivity. Leaks take longer to detect, and small leaks may go completely undetected.

Instead of relying on computational assumptions, the OptaSense pipeline leak detection system uses distributed acoustic sensing (DAS) technology to transform a standard telecommunication fiber optic cable into a fully distributed sensor capable of detecting the physical characteristics of a leak, including changes in noise, temperature, pressure and ground strain—simultaneously and in real time. The integration of these four modes into a single leak detection system not only provides improved sensitivity, it delivers the reliability required to identify and validate leaks faster and with more confidence so minor issues can be addressed before they become major incidents. The OptaSense system can detect small leaks 10 times faster than internal systems—allowing you to detect a 0.1% leak size within a matter of minutes.

Today’s complex pipeline networks require robust systems that perform under changing fluid compositions, temperatures and pressures, which for many internal systems often result in computational errors and false alarms. The OptaSense pipeline monitoring solution eliminates these issues by delivering a system that performs under transient, slack-line, and multi-phase flow conditions. Even when critical pipeline infrastructure goes offline, this fiber-based system ensures continuous and reliable real-time event detection, classification and location.

13 Jul 2017

Real-time Cluster Efficiency

Distributed fiber optic sensing for uniform fracture stimulation

Evaluating stimulation performance and well spacing early in development can increase a projects Net Present Value. This is especially true when developing stacked intervals.  For example, studies have shown that plug-and-perf completions often produce under-performing perforation clusters and undesired inter-well communication.

To address under-performing perforation clusters, operators are combining Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS)measurements to calculate the amount of fluid and proppant placed in each cluster on the fly to enable optimized decision-making throughout a project ensure more effective fracturing on current and future wells.

Recent observations from fiber optic DAS and DTS indicate that a majority of treatment volume is limited to only one or two dominate clusters near the heel-side of a treatment stage—leaving the remaining stage clusters under stimulated.

With a large majority of perforation clusters failing to contribute to production, you can’t help but ask: Where’s my proppant going and why?

Assessing cluster efficiency, fluid distribution and diverter effectiveness

There are many possible reasons for uneven reservoir stimulation, such as stress shadowing interference between fractures, local heterogeneity, the effectiveness of zonal isolation between stages, stimulation design (pumping schedules and fluid/proppant selection), and the variation in natural fracture systems surrounding the well.

Fiber optic monitoring, such as DAS and DTS can be used to assess cluster efficiency, fluid and sand distribution and diverter effectiveness.

On a recent spacing pilot in the Anadarko Basin, home to several stacked interval reservoirs, a five-well project equipped with OptaSense Distributed Fiber Optic Sensing offered another explanation for the heel-side bias. For this project fiber optic derived DAS and DTS measurements provided the operator an opportunity to monitor fluid movement during fracture stimulation and warm-back before the well was produced.

Monitoring distribution

During treatment, acoustic and temperature data confirmed inadvertent diversion away from toe-side clusters, and acceleration of the already-dominant heel-side clusters. Using algorithms applied to DAS data, proppant volumes per cluster were calculated revealing highly uneven proppant distribution among multiple clusters even when fluid is uniformly distributed

The DAS measurements captured in this pilot project suggested a strong heel bias was present in a majority of stages. The uneven distribution, caused by interference between adjacent fractures within a given stage and from preceding fracture stages, resulted in a consistent geometric predominance for fracture growth toward the most heel-ward perforation cluster.

A variety of completion variables, such as perforation designs, fluid systems, diverter and proppant size, were tested to identify the optimal treatment for improved fluid distribution.

Simulating distribution

Using these measurements, the operator used calculated proppant placement to monitor diversion efficiency in real-time during the fracture and took action to modify the treatment, which resulted in more even fluid and treatment distribution. After modeling the improved distributions derived from fiber optic monitoring, a new well completion and stimulation design resulted in more equal fracture heights and half lengths, as well as increased the overall effective fractures in the wellbore.

Multiple optimizations in pressure pumping strategy were discovered during the variable testing using real-time DAS and DTS. The pumping schedule was altered to test different rations of slick water and high viscous fluids, ratios in proppant sizes and concentrations of proppant within the various fluids.

Optimizing distribution

Using DAS and DTS to estimate fluid and proppant placement enabled the operator to identify the root problem and implement an effective proppant and fluid treatment (aligned with an optimized pressure pump schedule) that mitigated the uneven stimulation. The result, improved cluster efficiency and more uniform proppant/fluid distribution on current and future stages and wells.