bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liner-Drilling Technology Mitigates Lost Circulation Offshore Mexico
Authors: Carpenter Chris 
Published: February 2015

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 163418, ’Use of Liner-Drilling Technology as a Mitigation for Lost Circulation in the Faja de Oro (Golden Lane) Oil Fields Offshore Veracruz, Mexico,’ by L.F. Aguilera Naveja, Pemex, and Steven M. Rosenberg, SPE, and Marco A. Dominguez M., SPE, Weatherford, prepared for the 2013 SPE/IADC Drilling Conference and Exhibition, Amsterdam, 5-7 March.
This paper will demonstrate the benefit of liner-drilling technology used to drill and cement an operator’s 9?- and 7-in. liners in place, allowing for the continued development of oil reserves in the Carpa and Bagre fields of the Faja de Oro area offshore Veracruz, Mexico. Before the introduction of drilling-with-liner (DWL) technology, two previous wells drilled in the Carpa field encountered massive lost circulation and hole instability while drilling into the El Abra limestone, resulting in a total of 55 days of nonproductive time (NPT) for the two wells.
Introduction
Nine fields have been developed in the offshore Faja de Oro area of the Gulf of Mexico (Fig. 1). They are the Arrecife Medio, Isla de Lobos, Tiburon, Bagre, Atun, Morsa, Escualo, Marsopa, and Carpa fields, and to date the estimated cumulative production is some 210 million BOE of light crude ranging from 30 to 40°API from the El Abra Middle Cretaceous limestone.
Conversations: You Must Be the Change
Authors: Fattahi Behrooz 
Published: February 2015

President's column
The aging of our industry’s workforce and the near-term disappearance of the related knowledge base and experience are apparent when examining the data on SPE members’ age distribution (excluding student members).
Fig. 1 shows that the “big crew change” is well under way with the Baby Boomers* preparing to leave our industry. It is estimated that the potential outflux in the next decade will be as large as 50% of those who are currently employed in the industry. The chart also shows a developing second peak where Generation Y* enters the industry in recent years, with a low for the Generation X* segment of the workforce.
Our industry lost a generation of workers in the 1980s, and now it is obvious that the rate of skills replacement is not adequate. Demographics in other sectors are similar to SPE’s. Charles Davidson, the CEO of Noble Energy, says, “There are about three per cent of the American Association of Petroleum Geologists members who are around 80 years old, and we may be needing them!” (Rhodes 2007). To sustain a planned expansion in investment estimated at USD 200 billion over the next 15 years, the industry is poised to recruit a large number of new talent. According to Lee Hunt, president of the International Association of Drilling Contractors, just the offshore rigs currently under construction will require an additional 17,000 new people not currently employed in our industry (Duey 2008). This talent squeeze can slow down the industry’s growth.
The current economic downturn has only delayed the wave of retirements and has resulted in a slowdown in hiring that may have somewhat masked one of the most significant challenges facing our industry today—inspiring talented young people to join the industry and prepare to lead it into the future.
*Baby Boomers are those born in the mid 20th Century, following World War II. Generation Y is the group born during the period 1976–95. Generation X is roughly defined as those born during 1965–80.
Comments: Assessing the Spill
Authors: Donnelly John 
Published: February 2015

Editor's column
As the Deepwater Horizon disaster drags on, the oil and gas industry is trying to offer some perspective around what has become a politically charged incident.
During last month’s International Oil and Gas Conference and Exhibition in China in Beijing, the incident, its cause, and its implications came up several times in the hallways and during panel sessions. During the executive plenary session, several top executives offered their thoughts on the accident.
The spill will “go down as a very dark moment,” for the industry, said Matthias Bichsel, a member of the Executive Committee of Royal Dutch Shell and director of Projects and Technology for Shell International E&P, adding that the loss of life in the accident was the biggest tragedy. The industry has a strong track record of conducting deepwater operations safely and the processes and the technology are in place to continue that record. “We need to learn what happened, then fix what needs to be fixed,” he said.
Mark Albers, senior vice president of ExxonMobil, said it was “premature” for governments to rush toward more regulation because no one is sure exactly what happened yet. The oil and gas industry has drilled 14,000 wells in deep water, including some more challenging than the one that was the source of the accident. The fundamental question for the industry is to find the root causes of the accident and determine if there was something unique about this well that would lead to an adjustment in best practices, he said.
Andrew Gould, chairman and chief executive officer of Schlumberger, agreed that it is too early to assess what happened or what needs to be done. But he noted that the industry should work on uniformity of deepwater project planning and contingency planning. There are operators of different sizes operating offshore and the quality of project planning for deepwater projects varies, he said. The industry must “self-discipline” itself or be open to more regulation, he added. One unfortunate aspect of the accident is that it could make it more difficult to attract young people to the industry, Gould said.
Behrooz Fattahi, 2010 SPE president, has noted that many SPE members have inquired about the spill. “SPE will have a role to play in addressing technical issues resulting from the accident; however, SPE is not the right organization to deal with a short-term emergency response,” he said in a statement, adding that there already are a large number of qualified people from the industry who are working to resolve the situation. “SPE’s mission is sharing technical knowledge, and our strength is in providing a longer-term response. We help the industry to learn from incidents like this, and will serve an important role in providing a forum for discussions on changes needed in equipment, operating practices, training and other recommendations on how to prevent or reduce the impact of future oil spills.”
Benchmarking Industry Talent Needs
Authors: Soupa Oliver 
Published: February 2015

Talent & Technology
Since 2004, Schlumberger Business Consulting (SBC) has produced the SBC Human Resources (HR) Benchmark to assess the global supply and demand for petrotechnical professionals (PTPs; covering geosciences and petroleum engineering disciplines) and highlight best practices in talent management. This annual survey has become the reference point for industry professionals who seek talent strategies that have a measurable impact on business results. The survey has found its place within the SPE Talent Council,* whose members, some of whom participate in the survey, use the results as a basis for discussion to identify potential areas of industry collaboration to improve the quantity and quality of talent available.
The SBC copyrighted The Supply Chain of Talent (Fig. 1) is the cornerstone of the SBC HR Benchmark. This framework was established by SBC to provide a holistic and systemic way to understand and address overall HR challenges in the industry. Many SBC clients today adopt The Supply Chain of Talent in their HR planning and management processes to address difficult HR issues that have proven complicated in the past. Addressing all these HR components in an integrated way has resulted in a higher impact than a piecemeal approach.
The 2009 Benchmark results were presented during the annual SBC HR Forum in December. More than 20 global companies comprising national oil companies (NOCs), majors, independents, and 70 universities, which offer geosciences and petroleum engineering programs, participated in the survey. Three major observations were made based on the survey findings:
In the recent economic downturn, international oil companies (IOCs) decreased their recruitment targets more than NOCs, putting university oil- and gas-related programs at risk and possibly creating future talent gaps.
Oil and gas companies have taken steps to adjust their demographic profiles.
Coaching is a valuable tool to reduce the time to autonomy for PTPs.
*The SPE Talent Council was formed in 2007 to provide a forum in which industry, academia, and nongovernmental organizations could collaborate on initiatives to increase the quantity and quality of talent available to the industry.
Dynamic Updating of Reservoir Models
Authors: Denney Dennis 
Published: February 2015

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 123671, ’Dynamic Updating of Reservoir Models,’ by Harun Ates and Asnul Bahar, SPE, Kelkar and Associates, and Vitaly Krasnov, SPE, Rosneft, and Mohan Kelkar, SPE, University of Tulsa, prepared for the 2009 SPE Annual Technical Conference and Exhibition, New Orleans, 4-7 October. The paper has not been peer reviewed.
In sandstone reservoirs, an important challenge is scaling up a fine-scale model effectively. Conventional methods are not adequate when significant shale distribution exists in the reservoir. In the fine-scale model, some sand bodies are connected to the wells and some are not. As the fine-scale model is scaled up, some discontinuous sand bodies become combined with connected sands. A new procedure was developed to overcome this problem.
Introduction
Traditional reservoir modeling involves developing a fine-scale geocellular model that incorporates the small-scale static uncertainties. Once such a description is created, it is scaled up to an appropriate scale such that it can be flow simulated to understand the dynamic performance of the reservoir. It is difficult to flow simulate a fine-scale model because it is computationally demanding.
Some sandstone reservoirs tend to be highly discontinuous, with sand and shale dispersed within the reservoir. The continuity of the sand bodies may not be known precisely and reflects an uncertainty in static models. The problem becomes even more complex if the reservoir is thick and contains multiple thin sand bodies. When a fine-scale model is constructed, it may contain many vertical layers to account for all the thin sands present in the reservoir.
Scaling up of such models is very difficult because of the following.
If the model is coarsened (scaled up) significantly, many of the discontinuous sands will connect to other sands, and this will increase the pore volume (PV) “connected” to the wellbore, changing the transmissibility (connectivity) distribution between wells.
In the scaled-up model, because of artificially connected sands, infill wells would not indicate true potential of additional recovery because some of the virgin sands that would have been connected to the newly drilled wells would show to have been drained already by existing wells in the model.
If the model is maintained at relatively fine scale, the simulation can be computationally demanding. The dynamic modeling (e.g., history matching) would be more time consuming. Therefore, many uncertainties may not be investigated correctly.
Modeling Well Performance in Shale-Gas Reservoirs
Authors: Denney Dennis 
Published: February 2015

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 125532, ’Modeling Well Performance in Shale-Gas Reservoirs,’ by C.L. Cipolla, SPE, Carbo; E.P. Lolon, SPE, StrataGen Engineering; and J.C. Erdle, SPE, and V. Tathed, SPE, CMG, prepared for the 2009 SPE/EAGE Reservoir Characterization and Simulation Conference, Abu Dhabi, UAE, 19-21 October 2009. The paper has not been peer reviewed.
This paper focuses on modeling well performance in shale-gas reservoirs by use of numerical simulation. Stimulation treatments in many shale-gas reservoirs create very complex fracture networks. These fracture networks are required to achieve economic production rates from rock with a matrix permeability as low as 10 nanodarcies. The primary issues with modeling production from shale-gas reservoirs are describing gas flow from the tight shale matrix into the fracture network accurately, properly characterizing the matrix-block size (or fracture density) and the conductivity of the network fractures, and evaluating effects of stress-sensitive network-fracture conductivity and gas desorption.
Introduction
Gas shales are organic-rich formations that are both source rock and reservoir. Gas is stored in the limited pore space of these rocks, with a sizable fraction of the gas in place possibly adsorbed on the organic material. Typical shale-gas reservoirs exhibit a net thickness of 50 to 600 ft, have porosity of 2 to 8% and total organic carbon of 1 to 14%, and are found at depths of 1,000 to 13,000 ft. The success of the Barnett shale in the USA has illustrated that gas can be produced economically from rock that was previously thought to be source rock and/or caprock, not reservoir rock, leading to the development of many other shale-gas reservoirs, including the Woodford, Fayetteville, Marcellus, and Haynesville.
The economic viability of many unconventional gas developments requires effective stimulation of extremely low-permeability rock, typically 0.0001 to 0.00001 md. In most cases, economic production is possible only if a very complex, highly nonlinear fracture network can be created that effectively connects a large reservoir surface area to the wellbore. Many conventional hydraulic-fracture treatments use high-viscosity fluids to reduce fracture complexity and promote planar fractures, allowing the placement of high concentrations of large proppant. However, stimulation treatments in shale reservoirs use large volumes of low-viscosity fluid (water) to promote fracture complexity and place very low concentrations of small proppant. Hydraulic-fracture treatments in horizontal wells can require several million gallons of water and up to 1 million lbm of proppant pumped at rates of 75 to 150 bbl/min.
From Flowback to Fracturing: Water Recycling Grows in the Marcellus Shale
Authors: Rassenfoss Stephen 
Published: February 2015

In Pennsylvania, recycling water from wells in the Marcellus Shale has been transformed from a trend to an essential skill. The tipping point came in mid-April in a notice from the state’s Department of Environmental Protection (DEP) telling 15 public water treatment plants to stop handling waste water from wells in the Marcellus.
The order to the only public facilities treating water from fracturing was voluntary, but the intent was clear. In the letter, Michael Krancer, the DEP secretary said: “Now is the time to take action to end this practice.”
If there was any doubt, the US Environmental Protection Agency (EPA) followed up with a letter in May telling the state agency to make that a mandatory order. The federal agency said it would contact large oil and gas companies and the water treatment facilities to ensure they were no longer processing water that had flowed back after fracturing, and then disposing it in the state’s waterways.
At that time two-thirds of the water from fracturing was recycled in Pennsylvania, where water use for shale gas companies has become a battleground with environmentalists, politicians, and the people who live on the land holding enormous natural gas reserves. The industry was already moving toward recycling, said Pete Miller, water resources manager of the Marcellus Shale division at Range Resources, which reuses nearly all the water from its wells there. “When the standard came out, it was another push in that direction.”
The state’s letter sparked a rush by those who faced higher disposal costs because they could no longer have their waste water treated in state. “People are calling and telling me, ‘I’ve got to figure this out,’” said Dave Grottenthaler, general manager of Kroff Oil Services, a Pittsburgh water treatment specialist that got into fracturing water reuse early on. “I’ve been telling them for a while, you can reuse all your flowback and you will be safe.”
Range Resources is evidence to how fast this transition can happen. It first used a mixture of fracturing flowback water and fresh water in August 2009. In 2010, it said it reused 96% of its produced water in Pennsylvania.
Technology Focus: Reservoir Simulation (July 2011)
Authors: Crick Martin 
Published: February 2015

Technology Focus
Simulation is about building a mathematical model of the reservoir and then using it to predict, for the purpose of making decisions. That may be restating the obvious, but there are a few points that bear a little re-emphasis. First, it is only a model. Second, if the model does not predict adequately, it does not serve its purpose. There is a growing tendency in some quarters to use very simple models—mainly because they are faster. As my colleague Ed May recently put it, “I know everyone pushes for faster, faster, but doing it right has definite advantages.”
Following my recent move into well testing, I have been rereading the late Laurie Dake’s The Practice of Reservoir Engineering. Dake often is regarded as hostile to simulation, but what he really was about was understanding your assumptions, and using the most appropriate model for the decision to be made.
At the 2011 SPE Reservoir Simulation Symposium, many papers focused on re-examining original basic assumptions. Correcting or removing those assumptions (improving the model) often led not only to better predictions, but to faster simulation. For example: Is the most recent solution of the well model the best starting point for the next solution? As the industry develops more-complex reservoirs (e.g., shales, naturally fractured, and heavy oil), we are called on to apply our simulation tools to new environments, and we must check constantly that the assumptions that are implicit in those tools are still valid. For example: Do assumptions for light-oil flow in homogeneous sandstone also apply to gas flow in shale?
The need to check assumptions applies as much to the data as to the tools. In simulation support, we often see data sets in which hundreds of warning messages about bad data are ignored or even suppressed, and the complaint is about the final failure to converge. Is that discontinuity in the pressure/volume/temperature data really a property of the fluid, or just a measurement artifact?
A good way to consistently challenge your assumptions is to read the best of the best technical articles: JPT is here for you!
Reservoir Simulation additional reading available at OnePetro: www.onepetro.org
SPE 144401 • “Design and Examination of Requirements for a Rigorous Shale-Gas-Reservoir Simulator Compared to Current Shale-Gas Simulators” by Juan Andrade, SPE, University of Oklahoma, et al.
SPE 140882 • “Multilateral Complex-Well Optimization” by P.I. Crumpton, Schlumberger, et al.
SPE 137507 • “Reservoir Characterization and Flow Simulation of a Low-Permeability Gas Reservoir: An Integrated Approach for Modeling Tommy Lakes Gas Field” by H. Deng, University of Calgary, et al. (See Journal of Canadian Petroleum Technology, May 2011, page 32.)
SPE 141935 • “An Adaptive Newton’s Method for Reservoir Simulation” by Pengbo Lu, ExxonMobil, et al.
SPE 142093 • “A New Method To Model Relative Permeability in Compositional Simulators To Avoid Discontinuous Changes Caused by Phase-Identification Problems” by Chengwu Yuan, SPE, University of Texas at Austin, et al.
Modeling, Simulation, and Optimal Control of Oil Production Under Gas-Coning Conditions
Authors: Denney Dennis 
Published: February 2015

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 143520, ’Modeling, Simulation, and Optimal Control of Oil Production Under Gas-Coning Conditions,’ by Agus Hasan, SPE, and Bjarne Foss, SPE, NTNU; and Svein Ivar Sagatun, Bjorn Peter Tjostheim, Atle Svandal, and Cato Hatland, Statoil ASA, prepared for the 2011 SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, 23-26 May. The paper has not been peer reviewed.
Gas coning is the tendency of gas to impel oil downward in an inverse-cone contour toward the well perforations. After gas reaches the well, gas production will dominate the flow stream and oil production will decrease significantly. In this paper, the gas-coning process in a gas/oil reservoir (completed with a single horizontal well) is modeled, simulated, and analyzed by applying a nonlinear-control approach. The model that describes the well/reservoir interaction can be a boundary-control problem of the porous media with two boundary conditions: a Neumann boundary condition describing no flow at the outer boundary of the reservoir and a nonlinear-boundary condition describing the well’s production rate.
Introduction
Optimizing the trade-off between oil and gas production is important in reservoir management. The use of secondary-recovery techniques (e.g., gas lift and waterflood) and enhanced-oil-recovery techniques (e.g., surfactant injection) has proved successful for increasing oil production significantly. These techniques are supported by the use of smart-well technologies. A smart well is one that is equipped with several valves that can be regulated during production. Operating these valves can be accomplished by use of optimal-control theory, particularly when combined with the adjoint method. Adjoint-based optimization can be used to determine optimal well placement and for history matching. Optimal-control theory combined with data assimilation forms a closed-loop reservoir management.
Although providing solutions in a relatively short time and in an efficient way, the adjoint method is difficult to implement because one needs access to the reservoir-simulator code to implement the algorithm. An alternative is creating a mathematical model that is simpler but can be used to explain the same physical process. This model is referred to as a proxy model and serves as a representative of a complex model that usually is contained in a reservoir simulator. A proxy model may be derived from a basic principle of physics, such as mass conservation or Darcy’s law. The proxy model is simpler and easier to work with than the high-fidelity model.