bluuebunny/crossref_metadata_2025_split huggingface dataset:
So Many Wells, So Few Engineers: Scaling Production Engineering for all Those Shale Wells
Authors: Rassenfoss Stephen 
Published: December 2018

Shale plays present a daunting challenge for the small number of production experts charged with maximizing the output from this large population of fast-declining, quirky, and troublesome horizontal wells that are death to standard operating procedures.
On the face of it the industry has the problem in hand. Artificial lift systems are being installed early in the life of wells with strong initial production rates, followed by rapid declines that are supposed to flatten out to manageable levels when they reach 5 years old or so.
But there are no industrywide statistics to confirm if wells drilled recently are actually growing old at the single-digit rates that are widely assumed. Recently, though, Wood Mackenzie surveyed the decline rates of wells producing for more than 5 years in the Permian Basin and concluded the rate is around 14% a year.
As the population of old wells rises, interest in eking out more oil and gas from them appears to be up. The organizers of the recent SPE Artificial Lift Conference and Exhibition-Americas expected to draw 500 people and wound up registering more than 700 to the Houston-area event.
Much of the attention was on maximizing production from horizontal wells in ultratight rock by using better control systems and designs rather than focusing on improvements in the hardware. A key piece of those puzzles is developing ways of dealing with many wells where the performance varies erratically; monitoring, controls, and communication are often rudimentary; budgets are tight; and the physics of flow is still being figured out.
“The industry is finding out a lot of the older ways of working and older technical developments will not work for the horizontal wells at the scale we now have them,” said Anand Nagoo, president of Nagoo & Associates. He made the comment during a talk where he presented case studies of how his analytical multiphase flow model was applied in the wells of clients in unconventional development, including Equinor (SPE 190921, SPE 191772).
His critique was echoed in the description for an upcoming SPE Forum on Production in Horizontal Unconventionals: “While much investment has gone toward improving drilling and completions techniques, the industry still largely uses vertical well production techniques.”
Or as Steve Kennedy, production advisor at EOG Resources and the co-chair of the forum, said at a lunch where he was plugging the forum: “We need to get together and talk about it because these wells are” thoroughly disagreeable to deal with. Actually he put it more emphatically.
Two Engineers vs. 300+ Wells
There is money to be made in those troublesome old assets. With far more than 100,000 horizontal wells in the US, even small improvements can add up to some real money. Greg Leveille, ConocoPhillips chief technical officer, compared the process to the many small improvements that allowed drillers to slash the time needed to drill shale wells.
Shell Picks a Digital Platform To Build Its AI Future Upon
Authors: Jacobs Trent 
Published: December 2018

Alisa Choong, the chief information officer at Shell, recently told several hundred oil and gas professionals that “digitization is about making the right choices.”
Speaking on a panel at SPE’s Annual Technology Conference and Exhibition in Dallas in September, Choong shared that Shell has made one of those choices by signing a 3-year deal to use the enterprisewide analytics platform developed by Silicon Valley-based C3 IOT on Microsoft’s Azure cloud service.
The development comes on the heels of BP’s September announcement that is expanding the use of a competing analytics platform. Taken together, these cases reveal how large operating companies plan to manage and put into action their growing arsenals of machine-learning and artificial-intelligence (AI) programs.
For the past few years, the industry’s first movers have been assembling data science teams. As these teams and their capabilities mature, it has become clearer that they need a new kind of digital infrastructure that runs independent of the IT department.
“That’s fundamentally why Shell decided to standardize on the C3 IOT platform,” said Ed Abbo, chief technology officer and cofounder of C3 IOT. Seeing his firm’s platform as a “catalyst,” he added that Shell now has “a jumpstart on the market to operationalize these AI algorithms.”
After raising $100 million in equity funding earlier this year, C3 IOT has become one of the fastest-growing industrial analytics players. Its leadership also includes the billionaire entrepreneur Tom Siebel, who serves as chief executive officer and is most known for selling his previous software company, Siebel Systems, to Oracle for $5.8 billion in 2005. Abbo was involved in software development at both Siebel Systems and Oracle prior to starting C3 IOT with Siebel.
Scaling Up Shell’s AI
Shell began its trials with the C3 IOT platform by using it to automatically predict maintenance needs on dozens of gas compressors, which was successful in identifying failure risks up to 48 hours in advance.
The plan is now to expand this use case to hundreds of thousands of machines across the world—both on the company’s offshore facilities and onshore refineries. Additionally, Shell’s ambitions include using C3 IOT’s platform to support its supply chain and other digital initiatives involving computer vision and natural-language processing.
The ability to scale up this diverse set of applications is seen as the chief driver behind the adoption of enterprise-wide platforms. Founded in 2009, C3 IOT is among the earliest entrants into the platform space and is joined by a growing cast of competitors that include Arundo and GE Predix.
These companies are vying for their slice of the upstream market because most oil and gas companies of size store their data in hundreds or thousands of locations. The developers say that without an analytics platform, the job of ingesting, correlating, and keeping all these data sources updated in real time will keep industrial firms from launching algorithms across large bases of equipment and production systems.
Seeq’s Focus on Time-Series Data Draws in Chevron, Shell, and Pioneer
Authors: Jacobs Trent 
Published: December 2018

Time-series data historians have been a staple of industrial computing for almost 30 years. Yet today, this flavor of database technology has become more important than ever and is considered to be a linchpin of the Industrial Internet-of-Things (IIOT).
The predictive analytics market has seized upon this trend with the idea that intelligent computing programs can drive cash-generating insights out of these databases with little or no human supervision.
Seeq Corporation is taking a different approach to this concept by enabling humans to do what they already know how to do—only much faster. So far, more than 100 companies have bought into the 5-year-old firm’s software technology, including a growing number of the oil and gas industry’s most familiar names.
“Our focus is rooted in a really practical, natural intuition about how to work with data,” said Brian Parsonnet, the chief technology officer at Seeq. “We look not just at the analytics, but at what we would say is the ‘full arc’ of everything that goes into it.”
The oil field’s interest in the company was highlighted in July when it raised $23 million from a group of investors that included the venture arms of Siemens and Chevron.
The funding round also saw participation from Denver-based Altira Group, a venture capital fund that is closely aligned with several of the largest US shale producers: Apache, Devon Energy, and EQT. Pioneer Natural Resources, which also has strong ties to Altira, and international major Shell are two of the most notable producers who have announced that they are licensing the company’s software.
The Full Arc
The universal problem that the Seattle, Washington-based company says it has cured deals with the data that go into historians, which in the oil and gas context would commonly be temperature or pressure readings taken on a constant basis. The time-series (i.e., time-stamped) data are the vital signs of modern oilfield equipment, wellheads, and production facilities.
Amid the widening embrace of the IIOT, these historian databases have become the most rapidly expanding piece of the storage market, according to at least one analysis.
One thing to know about all this machine data is that they pile up quickly in the historians. That means for even the most routine root-cause analysis, it can it take a person weeks to access, connect, clean, model, give the data context (e.g., weather events or problems in ancillary systems), and then publish all these insights in a shareable report—this is the full arc Parsonnet refers to.
But when all this comes together the right way, the real story of how a complex system works together can finally be told. Seeq’s role is to shorten the time it takes to tell that story by making all those time-consuming steps easier and faster to complete. The role of discovering the big IIOT insights is then driven by a process or production engineer whose job it is to monitor and diagnose large production systems.
A Comprehensive Review Heavy Oil Reservoirs, Latest Techniques, Discoveries, Technologies and Applications in the Oil and Gas Industry
Authors: Temizel Cenk , Canbaz Celal Hakan , Tran Minh , Abdelfatah Elsayed , Jia Bao , Putra Dike , Irani Mazda , Alkouh Ahmad 
Published: December 2018

Petroleum in general is found in sub-surface reservoir formation amongst pores existent in the formation. For several years due to lack of information regarding production and technology, free-flowing, low viscosity oil has been produced known as conventional crude oil. Fortunately, in recent times, due to advancement of technology, high viscosity with higher Sulphur content-based crude has been produced known as heavy oil. There are also exists significant difference in volatile materials as well as processing techniques used for the two types of crude. (IEA, 2005; Ancheyta et al., 2007). The oil viscosity is a huge problem in regard to heavy oil as both recovery and processing charges increase proportional to Sulphur content and viscosity of the crude.
Heavy Oil can be used by definition internationally to describe oil with high viscosity (Although the Oxford dictionary might have several variations of the same, within the contents of this paper, we refer to heavy oil as high viscosity crude). Heavy oil generally contains a lower proportion of volatile constituents and larger proportion of high molecular weight constituents as compared to conventional crude oil (often referred to as light oil, we shall describe the characteristics of the types of oil further in the introduction). The heavy oil just doesn't contain a composition of paraffins and asphaltenes but also contains higher traces of wax and resins in its composition. These components have larger molecular structures leading to high melting and pour points. This makes the oil a bad candidate for flow profiles and adversely affects the mobility of the crude. (Speight, 2016). It is crucial to know the heavy oil constitution as it affects: Recovery: Low viscosity and high melting pointsProcessing: Higher Resin, Sulphur and aromatic contentTransportation: Low Viscosity
These all together impact the economics related to E&P (Exploration and Production) of heavy oil resources. These resources generally have a higher of production associated with them and are one of the first candidates to be affected by reduction of crude prices as seen in 2014 and early 2015. Crude oil can generally be classified into its types by using its API values that are generally obtained through lab testing. Table B1 provides a few popular crude types and their associated API Values.
Tackling High Water Production in Oman South Fields with New Technology
Authors: Sivrikoz Ayca , Jimenez Chavez Maria , Buwaiqi Salim 
Published: December 2018

Abstract
The subject field (Field NG) is one of the largest matured oil accumulations located in the South of Oman Salt Basin. Production and integrity issues have been the main challenge in recent years, manifesting in abnormal behavior of water-cut with time. Hence, detailed technical multidisciplinary studies were conducted in order to identify causes and propose mitigations.
The base historical performance of the field showed water cut progression behaving as a matrix block, however, in recent years new wells started showing unexpectedly higher initial water production (fracture like behavior). A thorough investigation was carried out utilizing numerical simulation models calibrated to Field NG production history in order to characterize the type of rock behavior (matrix behavior, conductive streaks, fractures, faults, etc). The study concluded that the water cut behavior was due to naturally-occurring fractures which are limited in length and not vertically extensive. During the early stages of production, when the initial water-cut shows matrix like behavior, the bottom water is not in contact with the fracture network. However, after years of production and rise of the water table, the fracture behavior became dominant as the water gets in contact with the small vertical fractures. The presence of these fractures were confirmed by a total of 11 FMI data taken since 2015.
The proposed solutions included detecting fractures early on using bore-hole imaging techniques and utilizing EZIPS in sealing as many fractures as possible. This completion method resulted in delayed water production and increased NPV by 2-3 $MM per well. Moreover, new and efficient WRFM technologies such as Autonomous Inflow Control Devices (AICDs) have been deployed in horizontal wells which selectively limit water flow. Initial results from the early implementations of AICDs are very encouraging.
Opportunity Assessment of a Deep Extra Heavy Oil Green Field: Scenarios for Life Cycle Cost Optimization Under Uncertainty and Risk
Authors: Ortiz-Volcan J. L. , Ahmed K. , Azim S. , Issa Y. , Pandit R. , Al-Jasmi A. K. , Hassan M. O. , Sanyal A. , Taduri S. 
Published: December 2018

Abstract
Selecting the optimum combination of technologies is a critical and challenging activity while conducting the opportunity assessment under high levels of uncertainty in a deep (~9000 feet) extra heavy oil green field transitioning between appraisal and development phases. Low mobility requires enhanced oil recovery to be addressed early in the life of the field, so selected wells can be drilled and completed in selected locations to reduce uncertainty about producibility and flow assurance.
This paper presents a practical approach to opportunity assessment based on Front End Loading (FEL) methodology, with three major steps: 1. Evaluation of known data, determination of complexities, uncertainties and risks by benchmarking with selected field analogs, 2. Identification of all potential technology options and 3. Definition of feasible appraisal and development scenarios and a high-level road map including estimates of life cycle cost opportunities for optimization.
We found reservoir static complexity medium, well complexity low, and reservoir dynamic complexity high. FEL definition indices for reservoir and well indicated low reservoir definition and acceptable index for wells. These complexity and definition indices were used for conducting benchmarking with three analog fields providing references for risks and ranges of production, recovery and total cost.
After multidisciplinary analysis with participation of 35 specialists organized into three clusters (subsurface, well and surface), 100 challenges (72 risks and 28 uncertainties) were identified, analyzed and ranked. Assessment of 36 parameters used for Enhanced Oil Recovery (EOR) screening were assessed from uncertainty perspective with preliminary selection of 7 potential EOR methods. Final integration was achieved with identification of 110 technology options for 30 key decisions, finally selecting best suitable options for 4 potential development chronological scenarios.
Results are presented in a cost breakdown structure reflecting the most critical cost drivers, where high percentage corresponds to OPEX affected by identified risks and causal maps describes effects on total costs for subsurface, well and surface. We modeled all significant risks by visualizing its impact on total cost and we defined the mitigation actions ranked by risk adjusted stochastic economics performed as input for decision-making.
This paper demonstrates that understanding the root causes of high cost per barrel and their relationship with uncertainties and risks during early stages of a heavy oil field life cycle, provides a common language for multidisciplinary cost optimization, and facilitates communication and involvement of all disciplines.
Investigating the Viscosity Reduction of Ultra-Heavy Crude Oil Using Hydrocarbon Soluble Low Molecular Weight Compounds to Improve Oil Production and Transportation
Authors: Fakher Sherif , Imqam Abdulmohsin , Wanas Ehab 
Published: December 2018

Abstract
Heavy oil reservoirs contain a large amount of hydrocarbons that are relatively difficult to produce and lift to the surface due to the very low mobility of these heavy oils. Even after producing these heavy oils, transportation problems arise as well due to the extremely high viscosities that these oils have. This research investigates the ability of several low cost chemical solvents to reduce heavy oil viscosity and also develops four novel formulations with high stability under harsh reservoir conditions and high solubility in crude oil to aid in the reduction of heavy oil viscosity and hence increase production from these reservoirs, and improve transportation of these heavy oils. A heavy crude oil from Kansas USA was used to conduct all experiments. The oil composition was determined using gas chromatography-mass spectrometry, and the asphaltene weight percent was determined using the conventional asphaltene solubility detection test. The pure chemical additives researched include kerosene, xylene, toluene, naphtha, and heptane. These chemicals were added with 5, 10, and 20 wt% to the crude oil, and the viscosity was measured using a viscometer at temperatures of 25, 40, 60, and 80 °C. The oil was found to have 5.73 wt% asphaltene, which is a good indication that the oil is heavy, since asphaltene is one of the heaviest components in the crude oil. Of all the pure chemicals used, toluene managed to reduce the oil viscosity the most, followed by xylene, then kerosene, and finally naphtha. Heptane could not be used since it had a very low boiling point, and thus evaporated very quickly, and also asphaltene was insoluble in it which resulted in a significant amount of asphaltene precipitation which would result in severe operational problems during the production operation. The novel formulations managed to reduce the oil viscosity significantly, however the pure toluene still showed slightly more oil viscosity reduction. The main advantage that the novel formulations had over the toluene however was their higher stability, even under harsh conditions due to the incorporation of a stabilizing agent within them. The main difference between the chemical compositions of the formulations was the concentration of the stabilizing agent, and the addition of some other chemicals. This research shows the capability of several chemical solvents to reduce heavy oil viscosity, and also develops four novel formulations with high stability to reduce heavy oil viscosity. These formulation can help increase oil recovery from heavy oil reservoirs, and also reduce lifting and transportation costs for these oil.
Hydraulic Dilation Stimulation to Improve Steam Injectivity and Conformance in Thermal Heavy Oil Production
Authors: Yuan Yanguang 
Published: December 2018

Summary
In thermal heavy-oil production, steam is injected to reduce oil viscosity and promote the less viscous oil flowing to the production wells. Steam injectivity and its conformance in the reservoir greatly impacts oil production and project economics. It is found that hydraulic dilation stimulation of heavy-oil reservoirs before steam injection can create a large and targeted stimulated reservoir volume for the steam to contact the heavy-oil phase. As a result, steam injectivity increases and steam conformance improves. These eventually translate to increased oil production and reduced steam/oil ratio, which has been proven in hundreds of wells worldwide. This paper describes relevant fundamental mechanisms and field performance.
As a major novelty, the hydraulic stimulation avoids fracturing the reservoir, but seeks to cause dilation. If the reservoir is fractured, a linear conduit is created. Steam can easily break through to neighbouring wells and the steam conformance is poor. When dilation takes place, however, additional pore space is created in the rock matrix. This results in truly volumetric stimulation, which is helpful to increase the steam injectivity while ideal thermal conformance is also achieved. This paper illustrates these theoretical bases and their resultant positive field performance in assisting thermal heavy-oil production.
Analytical and Numerical Models Assist in Water Production Management in a Heavy Oil Reservoir in Northern Kuwait
Authors: Al-Shammari Asrar Ajaimi , Kharghoria Arun , Garcia Jose Gregorio , Saikia Pabitra , Al-Shammari Abdulrahman Fares , Al-Rabah Abdullah Abdul , Husain Hisham , Kalia Devesh 
Published: December 2018

Abstract
A comprehensive numerical and analytical assessment of water coning in a heavy oil field in Northern Kuwait is presented in this study. Several wells were investigated in light of possible coning affect. Based on the lessons learned from the field data and modeling efforts, a coning envelope is generated and possible mitigation actions are explored. The complex geologic and stratigraphic architecture of the reservoir with underlying oil-water contact presents a unique challenge to achieve water-free oil production in this field. The field produces average 150 API crude of 50-100 cp at 100° F.
Production data from wells from different structural locations were history-matched using numerical simulations on single well models (including type well models). Model runs were extended to estimate critical liquid rate to avoid coning. Additionally, critical rates assessed from several analytical models were compared against those from the numerical simulations.
Critical liquid production rates for different areas of the field have been assessed based on the coning envelope generated. Further works showed that the critical rate is also a strong function of operational, reservoir and fluid parameters as well as completions standoff from current oil-water contact (OWC). Since the current oil API is very close to that of water, the critical rate is not a strong function of the density difference of the reservoir fluids, however, difference in the fluid viscosities displayed a some degree of impact on the coning rate. Operational results also showed that average of 15 ft standoff from the existing OWC is critical to avoid imminent coning. This presents an important opportunity for efficient completion decisions of a candidate well. The most significant new finding is that two analytical models evaluated during this study indicated that these models have limited capability to assess the critical rate from the heavy oil reservoir, and appear to have high degree of sensitivity to oil viscosity.
This paper provides an integrated approach to assess and manage water cone in a heavy oil recovery project. Generated coning envelope provides a tool for a proactive strategy for rate management including opportunities for strategic well completion decisions. Another noteworthy assessment is that the existing analytical models have significantly limited capability to model water coning behavior in a heavy oil reservoir.