This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30407, “Case Study of Nanopolysilicon Materials’ Depressurization and Injection-Increasing Technology in Offshore Bohai Bay Oil Field KL21-1,” by Qing Feng, Nan Xiao Li, and Jun Zi Huang, China Oilfield Services, et al., prepared for the 2020 Offshore Technology Conference Asia, originally scheduled to be held in Kuala Lumpur, 2–6 November. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. Nanotechnology offers creative approaches to solve problems of oil and gas production that also provide potential for pressure-decreasing application in oil fields. However, at the time of writing, successful pressure-decreasing nanotechnology has rarely been reported. The complete paper reports nanopolysilicon as a new depressurization and injection-increasing agent. The stability of nanopolysilicon was studied in the presence of various ions, including sodium (Na+), calcium (Ca2+), and magnesium (Mg2+). The study found that the addition of nanomaterials can improve porosity and permeability of porous media. Introduction More than 600 water-injection wells exist in Bohai Bay, China. Offshore Field KL21-1, developed by water-flooding, is confronted with the following challenges: - Rapid increase and reduction of water-injection pressure - Weak water-injection capacity of reservoir - Decline of oil production - Poor reservoir properties - Serious hydration and expansion effects of clay minerals To overcome injection difficulties in offshore fields, conventional acidizing measures usually are taken. But, after multiple cycles of acidification, the amount of soluble substances in the rock gradually decreases and injection performance is shortened. Through injection-performance experiments, it can be determined that the biological nanopolysilicon colloid has positive effects on pressure reduction and injection increase. Fluid-seepage-resistance decreases, the injection rate increases by 40%, and injection pressure decreases by 10%. Features of Biological Nanopolysilicon Systems The biological nanopolysilicon-injection system was composed of a bioemulsifier (CDL32), a biological dispersant (DS2), and a nanopolysilicon hydrophobic system (NP12). The bacterial strain of CDL32 was used to obtain the culture colloid of biological emulsifier at 37°C for 5 days. DS2 was made from biological emulsifier CDL32 and some industrial raw materials described in Table 1 of the complete paper. Nanopolysilicon hydrophobic system NP12 was composed of silicon dioxide particles. The hydrophobic nanopolysilicons selected in this project featured particle sizes of less than 100 nm. In the original samples, a floc of nanopolysilicon was fluffy and uniform. But, when wet, nanopolysilicon will self-aggregate and its particle size increases greatly. At the same time, nanopolysilicon features significant agglomeration in water. Because of its high interface energy, nanopolysilicon is easily agglomerated, as shown in Fig. 1.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 185640, “IOR Methods in Unconventional Reservoirs of North America: Comprehensive Review,” by Dheiaa Alfarge, Iraq Ministry of Oil and Missouri University of Science and Technology, and Mingzhen Wei and Baojun Bai, Missouri University of Science and Technology, prepared for the 2017 SPE Western Regional Meeting, Bakersfield, California, USA, 23–27 April. The paper has not been peer reviewed. In the complete paper, three stages of review have been combined to find out the applicability of the most-feasible improved-oil-recovery (IOR) methods in North American unconventional reservoirs. The study found that the integration of experimental, simulation, and pilot-test tools is the proper technique to accurately diagnose the most-feasible IOR methods in these reservoirs; these methods, as indicated by the research, include carbon dioxide (CO2), surfactant, and natural-gas injection. Review of Potential IOR Methods The ultratight matrix and high conductivity of natural fractures might be the two most important factors that impair success of conventional IOR methods. The authors conducted a critical review of more than 70 studies aiming to find applicability of different IOR methods in unconventional reservoirs. Chemical Methods. Generally, this category includes three methods: surfactant, polymer, and alkaline injection. Surfactant injection has the most-promising potential to improve oil recovery in North American unconventional reservoirs. These reservoirs are well-known as intermediate-wet to oil-wet; this type of rock affinity would prevent the aqueous phase from invading the matrix to displace the oil in place. Therefore, changing wettability and enhancing water imbibition through surfactant injection would be a good strategy to improve oil recovery. To the authors’ knowledge, there has been no study conducted to investigate the applicability of polymer- and alkaline-injection methods in these types of unconventional reservoirs. It is believed that injectivity problems are the primary reason that no investigation has been conducted on applying polymer in these reservoirs, although conformance problems are more dominant in the reported pilot tests. Also, injecting polymer into these reservoirs would plug the pore throats, which are very small in these plays. Investigation of alkaline potential in these reservoirs has also not been conducted by reported studies. This could be because there is no compatibility between this chemical agent and the mineral-composition complexity of these reservoirs. Smart-Waterflooding Technique. Recently, intensive studies have been conducted to investigate the effect on oil recovery of flooding with low-salinity water (LSW). It has been reported in different studies that maximum oil recovery can occur at optimal concentrations of salt for brine injected in cores (laboratory work) or in the field (simulation work). Wettability alteration and interfacial tension might be the main mechanisms behind the increment in oil recovery resulting from injection of LSW. However, the underlying mechanisms for wettability alteration are still controversial. Double-layer expansion and multicomponent ion exchange might be the main mechanisms behind wettability alteration because of the addition of salt. However, most of the reviewed studies focused on conventional reservoirs with high permeability.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 169039, ’Development of Small-Molecule CO2 Thickeners for EOR and Fracturing,’ by J.J. Lee, S. Cummings, A. Dhuwe, R.M. Enick, and E.J. Beckman, University of Pittsburgh, and R. Perry, M. Doherty, and M. O'Brien, General Electric Global Research, prepared for the 2014 SPE Improved Oil Recovery Symposium, Tulsa, 12-16 April. The paper has not been peer reviewed. The ideal carbon dioxide (CO2) thickener would be an affordable, safe, water-insoluble additive that could dissolve in CO2 at typical wellhead and reservoir conditions during CO2 enhanced oil recovery (EOR) and elevate the viscosity of CO2 to the same value as that of the oil. Further, the additive would not require heating or an organic cosolvent to achieve dissolution. In this paper, a strategy for designing a novel small-molecule CO2 thickener is detailed. Introduction Despite its longstanding success as an EOR technique, CO2 flooding does not recover all of the oil in the formation regardless of whether the reservoir has been waterflooded previously. Typically, primary recovery results in the production of approximately 5–15% of the original oil in place (OOIP), while secondary recovery is responsible for an additional 20–40% of OOIP. The fundamental causes of this disappointingly low oil recovery can be traced to the density and viscosity of dense CO2. First, the low density of high-pressure CO2 relative to oil promotes gravity override of the CO2, reducing oil recovery in the lower portions of the formation. Second, the viscosity of dense liquid or supercritical CO2 at typical CO2- flooding conditions is approximately 0.05–0.10 cp, a value so much lower than typical oil- and brine-viscosity values that it results in an unfavorable mobility ratio. This leads to viscous fingering, which in turn leads to early CO2 breakthrough, high CO2-usage ratios, delayed CO2 production, depressed oil-production rates, and low-percent OOIP recovery. These problems can be worse when the injection well is completed in two or more producing zones.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 194949, “Beam-Pump Dynamometer Card Classification Using Machine Learning,” by Sayed Ali Sharaf, Tatweer Petroleum; Patrick Bangert, SPE, Algorithmica Technologies; and Mohamed Fardan, Tatweer Petroleum, et al., prepared for the 2019 SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 18–21 March. The paper has not been peer reviewed. In reciprocating rod pumping systems, analysis of dynamometer-card data can deliver valuable insight into the status of the pump, and can indicate if future action is required. The complete paper explains the steps taken to improve surveillance of beam pumps using dynamometer-card data and machine-learning techniques, and reviews lessons learned from executing the operator’s first artificial intelligence (AI) project. Background The oldest and most widely used method of artificial lift is called beam pumping, or the sucker-rod lift method. A dynamometer is a device used on beam pumps that measures load on the polished rod (top) and plots the load in relation to the rod position as the pumping unit moves through a stroke cycle. This plot is known as the surface card. A pump card is a plot of load vs. position on the pump’s plunger. The pump card is more useful for surveillance purposes because it filters effects of anything above the plunger and provides standard pump card shapes for interpreting pump operating conditions. Identification and diagnosis of beam pumps using the pump card is an expensive human visual-interpretation process, not only requiring significant labor time but also deep expertise in the domain. Use of machine-learning techniques for pattern recognition can help automate the visual interpretation process, increasing efficiency and reducing maintenance activities resulting from missed early diagnosis. Data Collection Sucker-rod pumps are widely deployed in the Bahrain Field. There are two different types of communication layers used across the field, radio and optical fiber. Almost 300 optical-fiber- connected beam-pump units (BPUs) have been selected for surveillance and advanced analysis. Fiber is used to avoid any communication issues during data collection for the AI project. The sampling rate of collection for each pump is one reading per 20 seconds, thus covering three pump cards per minute. All BPUs are connected to a central server that converts hardware-communication protocol used by a programmable logic controller into the open-platform-communication (OPC) protocol. Fig. 1 shows the details of the 209 values representing a single pump card being read from a BPU and stored in the operator database. During the data-collection period, a total of 5,380,163 pump cards from 297 BPUs were collected and stored in the database. Data Labeling and Preparation In machine learning, an important step after data collection is data labeling, which is usually performed manually by experts. The labeled data set is used to feed machine-learning algorithms that detect patterns specific to each class. A total of 35,292 pump cards has been labeled (more than 1,000 cards per day on average). A useful feature of the labeling software is that it allows labeling an entire time period of cards in one shot, although such labeling should be performed with care.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 179690, “Viscosity and Stability of Dry CO2 Foams for Improved Oil Recovery,” by Chang Da, Zheng Xue, Andrew J. Worthen, Ali Qajar, Chun Huh, Mascarona Prodanovic, and Keith P. Johnston, The University of Texas at Austin, prepared for the 2016 SPE Improved Oil Recovery Conference, Tulsa, 11–13 April. The paper has not been peer reviewed. Carbon dioxide (CO2)/water foams are of interest for mobility control in CO2 enhanced oil recovery (EOR) and as energized fracture fluids or as hybrid processes that combine aspects of both processes. It is challenging to stabilize ultradry foams with extremely high internal-phase gas fraction given the high capillary pressure and the rapid drainage rate of the lamellae between the gas bubbles. However, the authors demonstrate that these ultradry CO2- in-water foams may be stabilized with surfactants that form viscoelastic wormlike micelles in the aqueous phase. Introduction In this study, the authors extend the study of ultradry CO2/water foams composed of worm-like micelles to higher temperatures by adding an electrolyte, potassium chloride (KCl), and a cationic surfactant, decyldimethylamine (C10DMA), to the primary surfactant, sodium lauryl ether sulfate (SLES). The continuous-phase viscosity and surface shear viscosity of this formulation were found to be approximately two orders of magnitude higher when worm-like micelles were formed at room temperature. The foam morphology was measured at high pressure with microscopy, and a long lifetime of foam bubbles was demonstrated. The morphology of the worm-like micelles was also characterized by cryogenic transmission electron microscopy. The authors have been able to manipulate foam stability for various specialty applications such as EOR where low water consumption, foam stability and extended life span, and conformance of the foams are crucial. In particular, these high-quality stable foams have been developed and tested at laboratory scale in high-salinity and high-temperature conditions to mimic the actual reservoir condition. These high-quality, highly stable foams have been generated and tested by use of sandpacks at the laboratory scale. In this work, a numerical simulation of foam injection into a layered reservoir is performed.