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Thank you for attending this Virtual SPE Workshop. The workshop provided opportunities for speakers to discuss current topics, share experiences based on the latest case studies, gain insights into best practices, and participate in informal debates amongst industry professionals. In addition, the workshop was an excellent occasion for participants to network with fellow peers and exchange ideas on recent industry trends and global geopolitical challenges. This workshop was the platform for discussion and sharing of ideas for a wide range of industry professionals, including practitioners of economics, corporate business planning, decision-making, regulation, legal, geosciences, engineering, and external consulting. It addressed existing and emerging practices on valuation techniques and approaches used in the petroleum economic assessment process, while making an investment opportunity and decisions viable and sustainable during a period of low oil price.
Process design of separation internals is just one step in improving the vessel performance. Just as important are the support design and installation steps. These lessons learned help to guide good off- and on-site planning to minimize separator turnaround. Troubleshooting and solving separation problems takes a combination of analytical tools, experience, and a knack for investigation. These 5 lessons provide a starting point for assessment.
YPF’s data analytics experts are eagerly seeking partnerships with oilfield operations experts who can help blend elegant data analysis with the messy reality of oil production. The international major has been playing with intelligent programs for years, but this new deal shows that it is now ready to scale those efforts up to cover hundreds of thousands of pieces of equipment. Pioneer's Analytics Project Reveals the Good and Bad of Machine Learning A recent research effort has shown that the digital journey is full of stumbling blocks. Just like humans, advanced computing technology will get some things right and some things wrong. Some operating companies are now enlisting engineers as foot soldiers in their analytics army.
Fed by big data loads from big operators, a university consortium and software firm are each working to make upstream data access as quick and easy as a Google search. Researchers have developed a drilling-data-aggregation and -distribution system that seamlessly integrates all forms of data, file types, and communication protocols and incorporates human-factors engineering in the design. In this study, the authors demonstrate a reliable, cost-effective methodology that empowers shale operators with reservoir data on every well. One of the biggest ways to lower the cost of production from shale would be to identify zones that are productive, or not, before fracturing them.
The industry is becoming increasingly complex, leading to changes in how universities approach education for undergraduate study. New research links a rise in seismic activity in West Texas with increased oil and gas development over the past 20 years and, in particular, the past decade. Fed by big data loads from big operators, a university consortium and software firm are each working to make upstream data access as quick and easy as a Google search. A new university-led consortium aims to bring together industry and academia to help operators efficiently orchestrate the final days of deepwater developments. Researchers at the University of Texas at Austin (UT) have set an audacious goal to halve the time, cost, and number of rig personnel required for drilling every type of well, from unconventional shale to ultradeepwater.
ConocoPhillips has pulled out of the much-hyped Louisiana Austin Chalk play after the company’s test wells yielded a gusher of water. Marathon Oil says its shale fields are producing more oil and gas with less hands-on work from company personnel thanks to a growing arsenal of digital technologies and workflows. Encana CEO Doug Suttles assures that shale executives are acutely aware of the parent-child well challenge, and he doesn’t think it’s “a big threat” to the sector.
The provider of subscription-based analytics services for the North American oil and gas sector continues its streak of purchasing data-focused firms. Findings from Kayrros suggest the average Permian well is both less productive and more expensive than reflected in public data. Fed by big data loads from big operators, a university consortium and software firm are each working to make upstream data access as quick and easy as a Google search. Is the Cloud Mature Enough for High-Performance Computing? Data volumes are growing at an exponential rate.
Warm solvent injection (WSI) has been proposed as a promising alternative to steam-based methods for bitumen recovery, due to its potential to reduce greenhouse gas emissions and environmental footprint. It involves injecting heated vaporized solvent (low molecular weight hydrocarbons) to reduce the viscosity of bitumen via solvent diffusion and latent heat transfer. However, similar to its thermal counterparts, the WSI recovery response is also highly sensitive to the underlying reservoir heterogeneities, e.g., shale barriers; in particular, the conformance of solvent chamber advancement can be a severe concern in heterogeneous reservoirs. Therefore, it is essential to approximate and monitor the development of solvent chamber during production and to optimize the operations design. Conventional monitoring methods, such as 4D seismic, can be quite costly. This work proposes a novel approach involving machine-learning techniques to efficiently track the solvent chamber positions in heterogeneous reservoirs.
First, a detailed sensitivity analysis is performed to examine the impacts of shale barriers on WSI production responses, which include the oil rate and the evolution of solvent chamber. A set of synthetic simulation models for the WSI process are constructed. Petrophysical, fluid and operational variables representing typical Athabasca oil sands conditions are assigned. Different configurations of shale barriers with varying sizes, correlation length and proportions are assessed. Next, a large training dataset consisting of many heterogeneous models and their simulation results are assembled. The inputs features are extracted from the oil production based on several time-series analysis methods; the output parameters are formulated to represent the dynamic evolution of solvent chamber. Different dimension reduction and parameterization strategies are formulated and tested to represent the solvent chamber locations and interfaces. Convolutional neural network is implemented to dynamically track the solvent chamber positions by correlating the extracted inputs and outputs.
The simulation results confirm that the presence of shale heterogeneities would impede the development of solvent chamber, causing a reduction in oil rate. In particular, the shale barriers that are located closer to the well pairs would exert a more severe impact on production responses than those that are located at further distances from the wells. The application of machine-learning algorithms enables the locations of the solvent chamber as a function of producing time to be inferred and tracked reliably. The proposed workflow provides a practical workflow to estimate the real-time solvent chamber development corresponding to the WSI process in heterogeneous reservoirs from oil production and solvent profile directly.
The presented workflow offers a novel alternative to infer the development of solvent chamber in heterogeneous reservoirs from production time-series data directly. This type of analysis could complement many existing monitoring techniques to deliver a more comprehensive inference of the distribution of shale heterogeneities in solvent-based bitumen recovery operations. Production data is used directly to assess the conformance of solvent chamber advancement, which is an important consideration in operations design and real-time optimization.
Schlumberger is getting rid of its struggling OneStim business unit 2 years after an acquisition that doubled its size. It will get 37% of the shares of Liberty Oilfield Services, which said it will be the second-largest player in that sector. The new geothermal project development company will offer expertise in subsurface and drilling, project development, and risk mitigation. A lot about the blowout preventers used for offshore drilling has changed since Macondo in 2010, but the essentials remain. This evolution serves as a case study on why some oilfield technology is hard to change.
Looking to market your technology? Engage partners, pursue all paths, and learn to catch smaller fish. From the highest courts of the US judicial branch to the C-suite, contests involving patents have recently come to the fore in the innovation hungry US oilfield services industry, even as filings and litigation have declined in recent years. Seeking out, experimenting with, and ultimately embracing technologies from other industries have proven crucial to innovating at oilfield service firms such as Halliburton, which has tried everything from dog food to submarine tech to improve its work downhole. R&D may be the key to the survival of companies as the new economics of the industry take hold.