Zhu, Daoyi (China University of Petroleum, Beijing) | Hou, Jirui (China University of Petroleum, Beijing) | Wei, Qi (China University of Petroleum, Beijing) | Chen, Yuguang (China University of Petroleum, Beijing)
The PG Reservoir in Jidong Oil Field is at a depth of approximately 4500 m with an extremely high temperature of approximately 150°C. The average water cut has reached nearly 80%, but the oil recovery is less than 10% after only 2 years of waterflooding process. It is of great importance to develop a high-temperature-resistant plugging system to improve the reservoir conformance and control water production. An in-situ polymer-gel system formed by the terpolymer and a new crosslinker system was developed, and its properties were systematically studied under the condition of extremely high temperature (150°C). Suitable gelation time and favorable gel strength were obtained by adjusting the concentration of the terpolymer (0.4 to 1.0%) and the crosslinker system (0.4 to 0.7%). An increase of polymer and crosslinker concentration would decrease the gelation time and increase the gel strength. The gelant could form continuous 3D network structures and thus have an excellent long-term thermal stability. The syneresis of this gel system was minor, even after being heated for 5 months at the temperature of 150°C. The gel system could maintain most of the initial viscosity and viscoelasticity, even after experiencing the mechanical shear or the porous-media shear. Core-flow experiments showed that the gel system could have great potential to improve the conformance in Jidong Oil Field.
Worldwide, workplace cancer prevention has a significantly lower profile than workplace injury prevention despite a real and present need to elevate the profile of workplace cancer prevention globally. Many organizations worldwide attest to the high number of annual work-related cancers and cancer deaths, but then say that workplace cancer statistics are underestimated, that the problem is worse than statistics bear out, and that the profile of workplace cancer prevention must be elevated. This apparent consensus begs a few questions. Supported by reputable resources from around the globe, this article explores several questions:
What Is Cancer & How Prevalent Is It?
According to the U.S. Department of Health and Human Services’ 14th Report on Carcinogens, cancer affects almost everyone’s life, either directly or indirectly; approximately one out of two men and one out of three women living in the U.S. will develop cancer at some point in his/her lifetime (NTP, 2016). According to American Cancer Society (ACS, 2017a), cancer is the second most common cause of death in the U.S. and accounts for nearly one of every four deaths. World Health Organization (WHO, 2017) estimates that worldwide in 2012 (the most recent data), 14 million new cancer cases and 8.2 million cancer-related deaths occurred, and that the number of new cancer cases is expected to rise by about 70% over the next 20 years.
Real-time drilling optimization is a topic of significant interest because of its economic value, and its importance increases particularly during periods of low oil prices. This paper evaluates different optimization strategies and algorithms for real-time optimization of an objective function (function to be optimized) specific to drilling. The objective function optimized here is derived from a data-driven (or machine-learning) model with an unknown functional form. A data-driven model has been used to calculate the objective function [rate of penetration (ROP)] because it has been shown to be more efficient in ROP prediction relative to deterministic models (Hegde and Gray 2017). The data-driven ROP model is built using machine-learning algorithms; measured drilling parameters [weight on bit (WOB), revolutions per minute (rev/min), strength of rock, and flow rate] are used as inputs to predict the ROP.
Real-time drilling optimization that is data-driven is challenging because of run-time constraints. This is perceived as a handicap for data-driven models because their functional form is unknown, making them more difficult to optimize. This paper evaluates algorithms depending on their ability to best maximize the objective (ROP) and their time effectiveness. Two simple yet robust algorithms, the eyeball method and the random-search method, are presented as plausible solutions to this problem. These methods are then compared with popular metaheuristic algorithms, evaluating the tradeoff between improvement in the objective (search for a global optimal) and the computational time of run.
Using results from the simulations conducted in this paper, we concluded that data-driven models can be used for real-time drilling despite their computational constraints by choosing the right optimization algorithm. The best tradeoff in terms of ROP increase as well as computational efficiency evaluated in this paper is the simplex algorithm. The ROP was improved by 30% on average with a variance of 2.5% in the test set over 14 formations that were tested.
Several tools and techniques exist to understand distributions of reservoir properties. Interwell tracer testing is one of the most common methods to obtain reservoir information from the amount of tracer produced. The capacitance/resistance model (CRM) is an analytical tool to estimate connectivity between producer/injector pairs from historical rates and, when available, bottomhole-pressure data in waterfloods. Because the CRM is a physically based, simple input/output model, its combination with tracer testing can provide insight into reservoir features.
To enable the CRM application to tracer flow, we incorporated tracer models, based on miscible-displacement theory, into the CRM. Reservoir properties are estimated as a result of the model fitting to produced-tracer data. In this paper, we present three tracer models: a dispersion-only (short-range autocorrelation) model, a Koval (long-range) model, and a combination of the two. To incorporate the tracer models into the CRM, we used two methods, serial fitting (CRM then tracers) and simultaneous fitting (CRM and tracers).
We applied these techniques to tracer data from 10 injectors and 10 producers of the Lawrence Field. Results suggest that interwell connectivity obtained from the CRM is in good agreement with the observed peak-tracer concentrations. All tracer models are capable of giving a good fit in most of the cases. After comparing the tracer models, we determined that the combined model can represent a tracer flow better than the other two models alone. We also found that the simultaneous-fitting method gives the best fit to total producer-rate data and tracer data. Simultaneous fitting mitigates the nonuniqueness of the fits, leading to an improvement of tracer matching. The reservoir properties obtained in this study (Koval factor and dispersion coefficient) also were analyzed and compared with those from previous measurements.
Liu, Hui-Hai (Aramco Services Company) | Lai, Bitao (Aramco Services Company) | Zhang, Jilin (Aramco Services Company) | Huang, Xinwo (Aramco Services Company) | Chen, Huangye (Aramco Services Company)
This work proposes an innovative laboratory method to measure shale gas permeability as a function of pore pressure, a key parameter for characterizing and modeling gas flow in a shale gas reservoir. The development is based on a solution to 1D gas flow under certain boundary and initial conditions. The details of the theoretical background, including formulations to estimate gas permeability and conceptual design of the test setup, are provided. The advantages of our approach, surpassing the currently available ones, include that it measures gas permeability (as a function of pressure) with a single test run and without any presumption regarding the form of parametric relationship between gas permeability and pore pressure. In addition, our approach allows for estimating both shale permeability and porosity at the same time from the related measurements. Numerical experiments are conducted to verify the feasibility of the proposed methodology.
Fiber-optic (FO) -based sensing technologies such as distributed temperature sensing (DTS) or distributed acoustic sensing (DAS) for well surveillance are attractive because they offer a continuous collection of real-time downhole data without the need for well intervention, thus avoiding production deferment. An example is the application of DTS and DAS for gas lift performance monitoring in oil producers by measuring the thermal and acoustic effects from the flow of lift gas through the valves into the production tubing to determine the active, inactive, and possibly leaking valves, and, also, the unloading depth. An anomaly observed in DTS data of a deepwater Gulf of Mexico (GOM) gas lifted oil producer led to a significantly improved interpretation methodology that allows inferring both the lifting depths and the annular-fluid interface(s). These results were confirmed by DAS, by identifying gas flow through a valve in selected acoustic-frequency bands. The new insights have been applied to five wells in the GOM and Southeast Asia.
Downhole temperature data obtained by either temperature logging or fiber-optic cables have been used to evaluate stimulation treatments and post-stimulation performance of horizontal wells with multiple fractures. Field cases qualitatively show capabilities of detecting creation of transverse fractures, poor zonal isolation, and inflow locations, although downhole temperature behavior in those wells is not fully understood from the theoretical modeling perspective.
In this study, we present comprehensive numerical flow and thermal models for a horizontal well with multiple fractures. The well experiences single-phase water flow during injection and shut-in, and gas/water two-phase flow during production. These models are formulated for reservoir and wellbore domains with consideration of their coupling. The reservoir models are formulated in 3D space using mass conservation of each component and thermal energy conservation with Darcy’s law in transient conditions. The wellbore models are also transient, and formulated for 1D space using mass conservation of each component, conservation of combined-phase momentum, and total energy conservation. The wellbore- and sandface-temperature profiles are obtained as solutions of these models. These models enable us to simulate field operations in multistage-fracturing treatment; injection and shut-in occur alternately for each stage from toe to heel with zonal isolation. After the stimulation treatments, these models are used to simulate temperature behavior during production in gas/water two-phase flow.
We show an example of a single fracture in which the developed model simulates temperature behavior during injection, shut-in, and production to show capabilities of the developed model. This study shows that injected fluid makes the fluid temperature in the fracture lower than the geothermal temperature even after 1 month of shut-in. This affects the temperature interpretation during production because the initial temperature is different from the geothermal temperature assumed as the initial temperature by most studies published previously. A synthetic case with five fractures demonstrates capabilities of detection of created-fracture locations from the shut-in temperature profile. In addition, we apply the model to a field case of distributed-temperature-sensor (DTS) temperature profiles during warmback after multistage hydraulic fracturing, and 30 days after the start of the production in this well. The good match obtained between this model and the DTS data from this well indicates how this modeling approach can be used to estimate the production from individual perforation clusters. The case studies illustrate qualitative interpretations in situations occurring in fields, such as warm-up behavior with multiple clusters during the shut-in period.
This paper provides insights from the theoretical modeling perspective for downhole temperature interpretation qualitatively performed at the current time. It also discusses the validity of the assumptions made in previous studies and precautions relevant to those assumptions.
Imagine it is a hot summer day and David the field technician receives an electronic text for a service call in the middle of his morning schedule. David adjusts his schedule to accomplish an assigned urgent task: the repair or replacement of a cooling fan for a natural-gas-fired HVAC unit atop the roof of a customer’s correctional facility.
Arriving at the work site 30 minutes later via a company vehicle, David positions an extension ladder to gain access to the client’s roof. He troubleshoots the HVAC unit and determines the malfunction to be a faulty bearing set. David climbs down to his vehicle to obtain the replacement part and returns to the roof with an extension cord and a reciprocating saw to complete the work. He locates a rooftop electrical outlet to power his saw and begins to disassemble the unit. When the repair is completed, David intends to return to ground level, lower and stow the ladder and proceed to a nearby fast food establishment to take his lunch break and cool off.
OSH professionals will quickly grasp the serious injury and fatality (SIF) hazard potentials that this worker encountered while working alone, remotely or in isolation. Consider the motor vehicle operation, ladder ascent/descent, fall from an elevated working surface, flammable gas under pressure, electrical contact through a power tool and extension cord, energized electrical HVAC components, unexpected HVAC start-up, workplace violence potential and heat stress exposure due to elevated temperature extremes.
The risk appetite of U.S. employers is maturing to recognize and respond to the hazards of lone work. Old business paradigms of minimal staffing to achieve maximum profits are being countered with wise risk management decisions to produce quality service and products in a safe manner.
An estimated 53 million people are lone workers in the U.S., Canada and Europe (Myers, 2015). Once OSH professionals begin pondering the topic, work environments and tasks for which lone work has been accepted in the past, despite the related SIF potentials, are easily identified and countered.
Kamal, Medhat M. (Chevron) | Morsy, Samiha (Chevron) | Suleen, F. (Chevron) | Pan, Yan (Chevron) | Dastan, Aysegul (Chevron) | Stuart, Matthew R. (Chevron) | Mire, Erin (Chevron) | Zakariya, Z. (Chevron)
A new method is presented that uses transient well testing to determine the in-situ absolute permeability of the formation when three phases of fluids are flowing simultaneously in the reservoir. The method was verified through simulation using synthetic data, and its applicability and practicality were confirmed through application to field data. Determining the absolute permeability over the reservoir scale using readily available transient testing data will have major benefits in accelerating history matching and improving reservoirperformance prediction.
A recently developed method (Kamal and Pan 2010) to determine the in-situ absolute permeability under conditions of two-phase flow extended the applicability of transient well testing and has been adopted in commercial software. In this study,
The method presented in this study uses surface flow rates and the fluid properties of the three phases. It also uses the same relative permeability relations used in the simulation models, thus ensuring that the same permeability values calculated from field data are used in history matching and predicting the performance of the reservoir. It is assumed that the fluid saturations are relatively uniform in the region around the well at the time of the transient test. The method was verified by comparing the input values with the results obtained from analyzing several synthetic tests that were produced by numerical simulation. Data from a deepwater field were also used to test the practicality and validity of the method. For the field case, the method was verified by matching reservoir production and pressure using the calculated absolute permeability. Excellent agreements were obtained for both synthetic and field cases.
Contractor prequalification is a “pre-tender process used to investigate and assess the capabilities of contractors to carry out a contract satisfactorily if it is awarded to them” (Hatush & Skitmore, 1997; Truitt, 2012). Written safety program submission is frequently required of contractors for review by hiring organizations or their third-party service providers as a condition of contractor prequalification. Consider a recent study of safety professionals in which more than 57% of respondents rated the evaluation of contractor written safety programs as being very or extremely important during contractor safety prequalification (Figure 1; Wilbanks, 2017). Programs required by hiring organizations regularly include evidence of contractor employee orientation, training and prejob task and risk assessment (Inouye, 2015).
Petersen (2001) might have ascribed the affinity for program submission as stemming from the “OSHA Era” of 20th century safety management evolution. He complained that overemphasis to programs with inadequate emphasis given to the humans who are subject to them inevitably results in workers not caring about safety. “And we wonder why our programs don’t fly! (p. 120).” Programs are not safety, Petersen (2000) retorts, they are “islands of safety,” normally in answer to the dictates of OSHA but not integrated into the overall management system. Petersen (2001) challenges the effectiveness of programs, asking: “Are they effective? Do they change attitudes or behavior? Do they motivate or even communicate?” (p. 117).
A present-day answering of Petersen’s questions in the context of contractor prequalification is aided by the observations of Philips and Waitzman (2013), who offer that requiring program submission may have some value (Table 1).