Central role of geophysics in 21stcentury exploration and production success

1999 ◽  
Author(s):  
Jeffrey D. Johnson
Keyword(s):  
Exploration And Production ◽  
Production Success

Experimental and Numerical Study of Coupled Dynamic Response of a Mini Tension Leg Platform

2004 ◽  
Vol 126 (4) ◽  
pp. 318-330 ◽  
Author(s):  
Anitha Joseph ◽  
V. G. Idichandy ◽  
S. K. Bhattacharyya
Keyword(s):  
Finite Element Method ◽  
Time Domain ◽  
Natural Frequencies ◽  
Numerical Study ◽  
Offshore Platforms ◽  
Wave Loading ◽  
Scaled Model ◽  
Wave Flume ◽  
Exploration And Production

Role of mini tension leg platforms (TLP) in oil exploration and production in marginal deepwater fields is becoming increasingly important. Mini TLP combines the simplicity of a spar and favorable response features of a TLP. In this paper, the results of a detailed experimental and numerical investigation of the coupled dynamic behavior of a mini TLP are reported with special attention to hull-tether coupling. The experimental study has been carried out using a scaled model in wave flume with specially designed tethers whose first two “string” natural frequencies are excited by waves, thus achieving strong hull-tether coupling. The numerical study has been carried out using a nonlinear time domain finite element method specifically addressed to compliant offshore platforms using a combination of potential theory based wave loading and Morison-type wave loading. Extensive comparisons between numerical and experimental results have been made both for platform motions and deflected shapes of the tethers and conclusions drawn.

Hedging, Investment Efficiency, and the Role of the Information Environment

2020 ◽  
pp. 0148558X2091633
Author(s):  
Gerald J. Lobo ◽  
Tharindra Ranasinghe ◽  
Lin Yi
Keyword(s):  
Oil And Gas ◽  
Investment Decisions ◽  
Information Environment ◽  
Investment Behavior ◽  
Investment Efficiency ◽  
External Financing ◽  
Data Set ◽  
Oil And Gas Exploration ◽  
Exploration And Production

Extant theories suggest that managers may use hedging either to alleviate underinvestment problems caused by costly external financing or to promote overinvestment by circumventing the scrutiny of external capital markets. We empirically investigate this issue using a hand-collected data set of hedging and investment behavior of oil and gas exploration and production firms. We do not find evidence that hedging alleviates underinvestment problems. However, we do find a strong positive relation between the extent of hedging and the propensity to overinvest. Further analyses indicate that the relation between hedging and overinvesting is stronger in settings where the firms’ information environment is more transparent. A more transparent information environment makes it easier for outside capital providers to distinguish between value-enhancing and value-destroying investment decisions so that greater discretion over internally generated funds becomes more valuable to overinvesting managers. Our study highlights the role of hedging in facilitating overinvestment and the conditions under which this role is likely to be more salient.

An Empirical Analysis of Artificial Intelligence, Big Data and Analytics Applications in Exploration and Production Operations

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Empirical Analysis ◽  
Oil And Gas ◽  
Oil Industry ◽  
Digital Transformation ◽  
Deep Dive ◽  
Exploration And Production ◽  
Oil And Gas Operations

Abstract Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an organization's ability to extract value from data. Extracting and analyzing data is getting harder as the volume, variety, and velocity of data continues to increase. Analytics can help us make better decisions, only if we can trust the integrity of the data going into the system. As digital technology continues to play a pivotal role in the oil industry, the role of reliable data and analytics has never been more consequential. This paper is an empirical analysis of how Artificial Intelligence (AI), big data and analytics has redefined oil and gas operations. It takes a deep dive into various AI and analytics technologies reshaping the industry, specifically as it relates to exploration and production operations, as well as other sectors of the industry. Several illustrative examples of transformative technologies reshaping the oil and gas value chain along with their innovative applications in real-time decision making are highlighted. It also describes the significant challenges that AI presents in the oil industry including algorithmic bias, cybersecurity, and trust. With digital transformation poised to re-invent the oil & gas industry, the paper also discusses energy transition, and makes some bold predictions about the oil industry of the future and the role of AI in that future. Big data lays the foundation for the broad adoption and application of artificial intelligence. Analytics and AI are going to be very powerful tools for making predictions with a precision that was previously impossible. Analysis of some of the AI and analytics tools studied shows that there is a huge gap between the people who use the data and the metadata. AI is as good as the ecosystem that supports it. Trusting AI and feeling confident with its decisions starts with trustworthy data. The data needs to be clean, accurate, devoid of bias, and protected. As the relationship between man and machine continues to evolve, and organizations continue to rely on data analytics to provide decision support services, it is imperative that we safeguard against making important technical and management decisions based on invalid or biased data and algorithm. The variegated outcomes observed from some of the AI and analytics tools studied in this research shows that, when it comes to adopting AI and analytics, the worm remains buried in the apple.

Internal multiple prediction using inverse scattering series withsparsity promotionPart II: Application strategy and field data examples

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Ole Edvard Aaker ◽  
Adriana Citlali Ramírez ◽  
Emin Sadikhov
Keyword(s):  
Inverse Scattering ◽  
Field Data ◽  
Norwegian Sea ◽  
Prediction Quality ◽  
Inverse Scattering Series ◽  
Exploration And Production ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
Seismic Images

Incorrect imaging of internal multiples can lead to substantial imaging artefacts. It is estimatedthat the majority of seismic images available to exploration and production companies have had nodirect attempt at internal multiple removal. In Part I of this article we considered the role of spar-sity promoting transforms for improving practical prediction quality for algorithms derived fromthe inverse scattering series (ISS). Furthermore, we proposed a demigration-migration approach toperform multidimensional internal multiple prediction with migrated data and provided a syntheticproof of concept. In this paper (Part II) we consider application of the demigration-migration approach to field data from the Norwegian Sea, and provide a comparison to a post-stack method (froma previous related work). Beyond application to a wider range of data with the proposed approach,we consider algorithmic and implementational optimizations of the ISS prediction algorithms tofurther improve the applicability of the multidimensional formulations.

Technoeconomic Model for Offshore Supply Operations

1988 ◽  
Vol 110 (2) ◽  
pp. 102-108
Author(s):  
S. S. Rahman
Keyword(s):  
Simulation Modeling ◽  
Systematic Approach ◽  
Weather Conditions ◽  
Vital Role ◽  
Event Simulation ◽  
Exploration And Production ◽  
Drilling Operations ◽  
Logistic Support ◽  
Economic Criteria

The vital role of logistic support for maintaining uninterrupted drilling operations is well known to offshore petroleum engineers. Moreover, its importance is growing as exploration and production activities are extended to progressively deeper water and harsher weather conditions. However, no systematic approach for ensuring effective logistic support has yet been realized. A method of studying the characteristics of logistic support and of designing a system for securing effective supply to an offshore rig is proposed. It is based on event simulation modeling of offshore supply operations, together with more conventional technical and economic models for yielding economic criteria which take into account a possible interruption of drilling operations. The method has been developed through a detailed investigation of each component of the supply operation and of the inherent problems. To evaluate the feasibility of the approach, an example has been provided.

scholarly journals Role of glucose in enhancing life and potency of Cirrhinus mrigala spermatozoa during cryopreservation

2015 ◽  
Vol 7 (1) ◽  
pp. 159-164
Author(s):  
C. Judith Betsy ◽  
J. Stephen Sampath Kumar ◽  
C. B. T. Rajagopalasamy
Keyword(s):  
Energy Supply ◽  
Physiological Saline ◽  
Control Group ◽  
Cirrhinus Mrigala ◽  
Production Success ◽  
The Difference ◽  
Energy Supplementation ◽  
Score Pattern ◽  
Motility Parameters

Cryopreservation of fish gametes is an emerging technology and breeding with cryopreserved gametes is advancement in fish seed production. Success of cryopreservation is evaluated by the post - thaw motility of the spermatozoa, an for which energy is required. Cryopreservation is known to cause changes in the seminal plasma that would alter the energy supply for the motility of the spermatozoa. Therefore, energy supplementation is found to be useful during cryopreservation. Cirrhinus mrigala spermatozoa were cryopreserved along with glucose as a co-cryoprotectant after 1:100 dilutions with 0.85% physiological saline as extender and Dimethyl Sulfoxide (DMSO) as cryoprotectant (85:15). The diluents contained glucose at four different concentrations, viz., T1 (0.25%), T2 (0.5%), T3 (0.75%) and T4 (1%). The diluted milt was equilibrated for 10 min at 5˚ C and loaded into 0.25 ml straws. The loaded straws were then frozen with LN2 vapour for 5 min and immersed in liquid nitrogen. Observations were made once in 7 days for 42 days on motility parameters based on which the duration, score, pattern and percentage were determined. The spermatozoa cryopreserved with glucose at 0.5% concentration showed the highest motility duration of 204±3.6 s whereas Control group showed motility duration of only 83.33± 4.5 s on 42nd day. The difference in motility duration was statistically significant (P>0.025).The present study revealed the benefits of adding glucose a t0.5% during cryopreservation as it could help in maintaining the motility duration and survival of spermatozoa.

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