The technical contributions highlighted this year focus on matrix stimulation of carbonate and unconventional reservoirs. Matrix stimulation encompasses pumping processes used to improve the connection between the wellbore and the reservoir. They are effective in a wide range of lithologies and have been successful in most types of completions—cased and open hole, horizontal and vertical, simple and complex, injectors and producers. Wells are matrix stimulated during completion and to remove production- or injection-induced impairment. The defining characteristic of matrix stimulation is the use of chemical systems to dissolve material in the near-wellbore region pumped below pressures that propagate reservoir fractures. Three papers are presented in this feature, and several others are referenced for the interested reader.
One of the papers, SPE 168198, “The First Visualization of Acid Treatments on Carbonates With 3D Nuclear-Magnetic-Resonance Imaging,” provides a detailed description of the application of cutting-edge technology to image acid-induced wormholes in carbonates. While this technology is new, it offers the promise of quantifying the effect of wormholes on near-wellbore flow to a degree that has not been possible until now. (See also SPE 171699, “NMR as a Characterization Tool for Wormholes: The Complete Picture.”)
While the industry has focused on fracture stimulation of unconventional reservoirs, SPE 173640, “Monitoring Acid-Stimulation Treatments in Naturally Fractured Reservoirs With Slickline Distributed-Temperature Sensing,” demonstrates the value of matrix stimulation in a shale reservoir. It is a good example with some excellent data on distributed-temperature-sensing profile monitoring, and it shows how naturally fractured reservoirs, which have generally been a challenge for stimulation, can be addressed. Distributed-temperature-sensing technology continues to develop, and a number of papers have been presented in the past year describing new capabilities and interpretation methods. (See, for example, SPE 173686, “Optimization of Matrix Acidizing With Fluids Diversion in Real Time Using Distributed-Temperature Sensing and Coiled Tubing”; SPE 172546, “Setting a New Milestone in Carbonate Matrix Stimulation With Coiled Tubing”; and SPE 171021, “First Installation of Efficient and Accurate Multilaterals-Stimulation Technology in Carbonate Oil Application.”)
The stimulation process can also be improved by applying classical concepts from reaction engineering and other disciplines. Paper SPE 171766, “Challenge of Acidizing Horizontal Wells in Tight Carbonate Reservoirs: Weak Acid and Nonacid Alternatives,” is an excellent example. The lesson is to look in both directions, back to the technical basics and forward to embrace new technologies.
Recommended Additional Reading
SPE 171699 NMR as a Characterization Tool for Wormholes: The Complete Picture by Yaser Al-Duailej, King Fahd University of Petroleum and Minerals, et al.
SPE 173686 Optimization of Matrix Acidizing With Fluids Diversion in Real Time Using Distributed-Temperature Sensing and Coiled Tubing by Eber Medina, Pinnacle, et al.
SPE 171021 First Installation of Efficient and Accurate Multilaterals-Stimulation Technology in Carbonate Oil Application by Kevin Rice, Fishbones, et al.
Lee Morgenthaler, SPE, Senior Staff Production Chemist, Shell
01 June 2015
Factory-Model Approach Improves Performance of Coiled-Tubing Drillout
This paper presents a factory-model approach to improving CT drillout performance that has been used successfully for more than 3 years and has become standard practice.
Real-Time Formation-Face-Pressure Analysis Improves Acid-Fracturing Operations
This paper contains a detailed discussion of methods and a software tool that has been developed to generate information that predicts formation-face pressures in real time with the help of live bottomhole-pressure data.
The fourth industrial revolution is taking the oil and gas business by storm. Many companies have increased resources for big-data analytics and machine learning. Though no one sees physical oilfield services as in decline, development in these areas may take a back seat to artificial intelligence.
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