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A single velocity function cannot represent variations caused by major changes in depositional conditions such as changes from siliciclastic to carbonate deposition or vice versa. An example is the Texas Gulf Coast-2 well: the rocks below about 4.2 km are predominantly carbonate whereas above this they are mainly sand-shale siliclastics. To fit this situation with some sort of average function will give velocities that are too high in the siliciclastic portion and too low in the carbonate section. Problems will also be encountered because of the velocity inversion at about 2.9 km where a thick, low-velocity marine shale is encountered. A thick shale section may also restrict compaction and the release of interstitial water, causing overpressuring and consequent abnormally low velocities.
- Information Technology > Knowledge Management (0.40)
- Information Technology > Communications > Collaboration (0.40)
The drilling-fluid system--commonly known as the "mud system"--is the single component of the well-construction process that remains in contact with the wellbore throughout the entire drilling operation. Drilling-fluid systems are designed and formulated to perform efficiently under expected wellbore conditions. Advances in drilling-fluid technology have made it possible to implement a cost-effective, fit-for-purpose system for each interval in the well-construction process. The active drilling-fluid system comprises a volume of fluid that is pumped with specially designed mud pumps from the surface pits, through the drillstring exiting at the bit, up the annular space in the wellbore, and back to the surface for solids removal and maintenance treatments as needed. The capacity of the surface system usually is determined by the rig size, and rig selection is determined by the well design. For example, the active drilling-fluid volume on a deepwater well might be several thousand barrels.
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A Method of Obtaining Biological Inspiration to Improve the Performance for TALOS Wave Energy Converter
Zhang, H. (Marine Engineering Equipment College, Zhejiang Ocean University) | Sheng, W. A. (Lancaster University Energy Engineering, Renewable Energy Group and Fluid Machinery Group, School of Engineering) | Aggidis, G. A. (Lancaster University Energy Engineering, Renewable Energy Group and Fluid Machinery Group, School of Engineering)
ABSTRACT Most creatures are highly adapted to the environment for survival through the evolutionary process and developing useful biological features for design inspirations could improve the performance of Wave Energy Converters (WECs), such as the TALOS WEC. A method of obtaining biological inspiration to conceive novel design is provided in this paper. The current situation of wave energy utilization is described and a number of problems in the research and development of WECs are introduced. The structure, motion and other characteristics of TALOS WEC are analyzed. Finally, the method is validated with TALOS WEC followed by discussion and conclusions. INTRODUCTION More than 70% of the area on the earth's surface is oceans, which embrace abundant renewable energy resources. However, how to effectively utilize and extract the rich ocean energy has been a concern of researchers in various countries (Melikoglu, 2018). Ocean energy can be captured in many different ways, such as wave energy, tidal range energy, temperature difference energy and ocean current energy. Among ocean energy capture methods, wave energy has a longer duration, more energy and a wider distribution. Therefore, its huge application potential has yet to be mined (Jin and Greaves 2021), with the vast resources to be explored. Based on Mørk, Barstow, Kabuth and Pontes (2010), the global wave energy can reach 32000TW/yr. In order to effectively extract wave energy for electricity generation, wave energy conversion devices have been and are emerging in various concepts. For example, China, the United Kingdom, the United States, Australia, Japan and Norway and other countries have developed a variety of wave energy conversion devices (Zhang, Aggidis, 2018). Many devices can convert wave energy into electrical energy, but the progress in the commercialization is very slow (Lopez, Andreu and Salvador, 2013), mainly due to the difficulties in extracting wave energy efficiently, and the rate of performance and cost of WECs cannot meet the user requirements (Zhang, Zhao, Sun and Li, 2021).
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The Application of the Lognormal Cumulative Distribution Function (LCDF) for Time-Rate Interpretation and Forecasting of Wells in Uncon-Ventional Reservoirs
Waters, David (Southwestern Energy) | Bryan, Eric (DeGolyer and MacNaughton) | Symmons, Dave (Wilcox-Wiggins) | Ilk, Dilhan (DeGolyer and MacNaughton) | Blasingame, Thomas A. (Texas A&M University)
Abstract The primary objective of this work is to present a new DCA model adapted from the classic Lognormal Cumulative Distribution Function (LCDF) (NIST [2012], Wikipedia [2023]), where the base result is given by: (Equation) The proposed LCDF-DCA model was proposed by the first author of this work by subtracting the LCDF relation from unity (1), and then multiplying by a maximum scale value (i.e., the qi,LCDF parameter), this yields: (Equation) Or in its more compact form: [using erfc(x) instead of erf(x)] (Equation) Where: qi,LCDF = Initial rate (Vol/D) erf = Error function (Abramowitz and Stegun [1972]) (dimensionless) erfc = Complimentary error function (Abramowitz and Stegun [1972]) (dimensionless) μLCDF = Model parameter (μ = median LCDF parameter relation) (ln[t]) σLCDF = Model parameter (σ = standard deviation for LCDF parameter relation) (dimensionless) The simplicity (and robustness) of the qLCDF(t) model suggests that this could be a very effective DCA model, which could serve as a compliment or a supplement to the existing family of "distribution function" DCA models (i.e., the stretched exponential/power-law exponential model, the Logistical Growth Model, and the Weibull model). As a methodology, the "qDbQ" plot is used to compare and contrast behavior between various model and data functions. The qDbQ plot is a log-log plot with rate [q(t)] and cumulative [Q(t)] plotted on the left-hand scale and the decline parameter [D(t)] and the decline exponent [b(t)] are plotted on the right-hand axis. The model rate function [q(t)] is the basis function, and all of the other functions are computed from q(t) — the D(t) and b(t) functions are computed using analytical relations derived from the qLCDF(t) model (and validated using high-precision numerical calculations). Unfortunately, the form of the qLCDF(t) model cannot be integrated analytically, and we are left only with numerical integration — but again, this is performed with high-precision methods (as were the derivatives required for the numerical validations of the D(t) and b(t) functions). In short, we are highly confident of our ability to compute the qLCDF(t) model and its auxiliary model functions (i.e., the Q(t), D(t), and b(t) functions). In addition to the qDbQ functions, we also use the q’, qavg, and qavg′ functions on the qDbQ plots for the LCDF-only matches. In terms of applications, of testing/applying the new qLCDF(t) model, we provide 13 example cases — 1 tight gas case (East Texas), 1 Wolfcamp (TX) oil well case, 1 Appalachian gas well case, 3 Eagle Ford (TX) oil well cases, 5 cases from the SPE Data Repository (these are anonymous data donations for shale gas and shale oil wells), and 2 historical test cases from the petroleum literature. For cases, the Lognormal Cumulative Distribution Function (LCDF), the Modified-Hyperbolic (MH), and the Power-Law Exponential (PLE) DCA models were successfully applied using the qDbQ (log-log) plot approach. The LCDF model generally lies "between" the MH and PLE models in terms of its comparative performance in a visual sense — however; for several cases the LCDF model yielded superior matches for the D(t) and b(t) parameter function trends [as well as for q(t) and Q(t)], indicating that the form of the LCDF relation may be advantageous in general applications for forecasting and estimation of EUR for shale wells.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.46)
- Information Technology > Information Management (0.35)
- Information Technology > Communications (0.34)
Summary High-speed-rotor dynamic pump operation for downhole or surface production is required and also beneficial to handle very high gas volume fraction (GVF) flows. Operating speeds of these pumps can be in excess of twice those of conventional pumps. This study presents results showing that a high-speed helicoaxial pump (HAP) can operate satisfactorily at intake GVFs of up to 98%. The findings increase capabilities of field engineers and operators to boost and maximize production from high gas content wells. The HAPs tested had a 4-in. housing outer diameter (OD) and shaft rotational speed of 6,000 revolutions per minute (RPM). HAP rotor and diffuser clearances were 0.010 and 0.020 in. A water sprayer was included at the HAP inlet. Water volume flow rates were held constant and that for air was varied. Water volume flow rate range was 63 to 143 B/D, and 549 to 3,238 B/D for air. Intake pressures varied from 14 to 76 psig, and average temperature across the HAPs was 20°C. The corresponding measurements were recorded during observed stable pump operation for each test point. The results showed that the HAPs had stable operation during the tests for intake GVF range from 79 to 98%. The range of dimensionless pressure boost (DPB) was between 0.0184 and 0.0501, indicating that at such high speeds, the HAPs were able to add energy to the fluid even at high intake GVFs. For a given intake gas/liquid density ratio, the DPB decreased with increasing intake GVF. For the same liquid flow coefficient and intake GVF, increasing the intake gas/liquid density ratio increased the DPB of the HAP. The higher intake density ratio enhanced the HAP’s capability to provide positive pressure boost up to an intake GVF just above 98%. It was also observed that the HAP with the tighter diffuser-rotor clearance of 0.010 in. had a higher pressure boosting capability than the HAP with 0.020-in. diffuser-rotor clearance. Proper pump intake flow conditioning and homogenization using the water spray facilitated stable operation of the HAPs. Overall and in conclusion, running HAPs at high speeds in addition to optimizing certain features of the HAPs can result in stable pump operation and enhanced pressure boosting in high GVF flows. This study mainly highlights the importance of operating HAPs at high speeds of up to 6,000 RPM. Tightening clearances between rotordynamic components and tailored inlet flow conditioning are also additional features that enhance pressure boosting. This architecture opens up opportunities for field operators and engineering personnel to maximize hydrocarbon production from their very high gas content field assets, thereby increasing the economic bottom line for the stakeholders.
- North America > United States (0.94)
- Asia > Middle East > Saudi Arabia (0.68)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Production and Well Operations > Artificial Lift Systems > Hydraulic and jet pumps (1.00)
- Production and Well Operations > Artificial Lift Systems > Electric submersible pumps (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Downhole and wellsite flow metering (0.84)
Abstract Wellhead control panel ensures safe operation of Oil /Gas well operations. Digitalization of wellhead control panels helps in reducing the downtime. Distributed Control System ( DCS) can be used for collecting the wellhead control panel data and to perform panel health assessment. It triggers maintenance request / short messaging service ( SMS) once it identifies fault / trip. This paper analyses on how digitalized well head control panel maintenance can be carried out and how it reduces well down time considerably.
Since its reintroduction by Pratt (1999), full-waveform inversion (FWI) has gained a lot of attention in geophysical exploration because of its ability to build high-resolution velocity models more or less automatically in areas of complex geology. While there is an extensive and growing literature on the topic, publications focus mostly on technical aspects, making this topic inaccessible for a broader audience due to the lack of simple introductory resources for newcomers to computational geophysics. We will accomplish this by providing a hands-on walkthrough of FWI using Devito (Lange et al., 2016), a system based on domain-specific languages that automatically generates code for time-domain finite differences.
The Laplace transform of the diffusion equation in radial coordinates yields a modified Bessel's equation, and its solutions are obtained in terms of modified Bessel functions. This page introduces Bessel functions and discusses some of their properties to the extent that they are encountered in the solutions of more common petroleum engineering problems. A solution of Bessel's equation of orderv is called a Bessel function of order v. Of particular interest is the case in which λ ki so thatEq. Eq. 3 is called the modified Bessel's equation of order v.
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A properly designed and maintained drilling fluid performs essential functions during well construction such as transporting cuttings to the surface, preventing well-control issues and wellbore stability, minimizing formation damage, cooling and lubricating the drillstring and providing information about the wellbore. Transporting drilled cuttings to the surface is the most basic function of drilling fluid. To accomplish this, the fluid should have adequate suspension properties to help ensure that cuttings and commercially added solids, such as barite weighing material, do not settle during static intervals. The fluid should have the correct chemical properties to help prevent or minimize the dispersion of drilled solids, so that these can be removed efficiently at the surface. Otherwise, these solids can disintegrate into ultrafine particles that can damage the producing zone, and impede drilling efficiency.
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Green's function and source functions are used to solve 2D and 3D transient flow problems that may result from complex well geometries, such as partially penetrating vertical and inclined wells, hydraulically fractured wells, and horizontal wells. The point-source solution was first introduced by Lord Kelvin[1] for the solution of heat conduction problems and was extensively discussed by Carslaw and Jaeger.[2] The point-source solution is usually obtained by finding the limiting form of the pressure drop resulting from a spherical source as the source volume vanishes. In our terminology, a source is a point, line, surface, or volume at which fluids are withdrawn from the reservoir. Strictly speaking, fluid withdrawal should be associated with a sink, and the injection of fluids should be related to a source. Here, however, the term source is used for both production and injection with the convention that a negative withdrawal rate indicates injection.
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