Besides the rapid developments in the energy industry, there are substantial technological advances. The energy industry is calling for a strategic transformation of operation and business models through digital technologies and integrated data…
With the advent of the digital era, oil companies have invested more in obtaining and integrating basic data, and constantly improved the utilization of big data analytics, as an emerging trend, in oil and gas industries, with a view to discovering…
In less than a decade, there has been a tremendous evolution in the various storage solutions used to contain wellsite data in the upstream oil and gas industry. Many organizations from wellsite data management providers to the oil and gas operators…
Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive.…
Establishing a Big Data Analytics environment for Drilling operations is impacted by many factors such as the nature of drilling operations that requires quick decision making and has a diversity of data sources. This paper goes over the process of…
When changes happen to big data analytics (BDA) applications in the Cloud at runtime, the affected BDA applications have to be re-deployed to accommodate the changes. Deciding the most suitable deployment is critical and complicated. Although there…
With recent developments in data acquisition and storage techniques, there exists huge amount of available data for data-driven decision making in the Oil & Gas industry. This study explores an application of using Big Data Analytics to establish the…
Current multistage hydraulic fracturing operations in shale are costly, environmentally challenging and inefficient. Multistage hydraulic fracturing operations already represent close to 60% of the total drilling and completion cost for each shale…
In recent years, there has been a proliferation of massive subsurface data sets from sources such as instrumented wells. This places significant challenges on traditional production-data-analysis methods for extracting useful information in support…
Performance prediction is one of the important contents of oilfield development. It is also an important content affecting investment decision-making, especially for offshore oilfields with large investment. At present, most oilfields in China have…
With the continuously progressing of building the intelligent oilfield and the rapid development of the Internet of Things and big data technology, the emerging technologies such as the information acquisition, distributed computing and data mining…
The value of global environmental services may change by 30-50$billon depending upon global strategies of growth, and the degree of stewardship versus naked market forces. While corporations and governments claim holistic care and responsibility for…
Our definition of 'The Big Data' is the ability of having all the data set at the point of decision-making.Several documented research shows that less than 5% of all the data acquired in the oil and gas industry areactually utilised. Despite these…
In recent years, there has been a proliferation of massive subsurface data from instrumented wells. This places significant challenges on traditional production data analysis methods for extracting useful information, in support of reservoir…
Based on the big data theory and data mining of gas pipeline failure history, the key factors determining the safety of pipeline system are found out, such as probability, function, time and prescribed conditions. Based on the reliability principle,…
with the advent of the era of big data, people's way of thinking and habits have changed greatly. In Colleges and universities, big data has the characteristics of massive, high growth and diversity. Colleges and universities should seize the…
In less than a decade, there has been a tremendous evolution in the various storage solutions used to contain wellsite data in the upstream oil and gas industry. Many organizations from wellsite data management providers to the oil and gas operators…
In this paper, an optimization method based on big data was proposed to improve the desulfurization selectivity and reduce the energy consumption of traditional acid gas sweetening technologies. At first, decision-making parameters which have…
Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive.…
Petroleum exploration and production processes typically generate enormous amounts of petro-Technical data using sub-surface and surface sensors. The acquisition, transferring, managing, and interpreting of these huge sensor data, as well as the…
Establishing a Big Data Analytics environment for Drilling operations is impacted by many factors such as the nature of drilling operations that requires quick decision making and has a diversity of data sources. This paper goes over the process of…
Many methods have been proposed for leak detection in pipelines. The method based on the acoustic signals created by the leakage is a non-destructive method and has presented reliable results. However, applying such a method in noisy environments is…
The history of oil and gas development and production is a history of data development. The generation of a large amount of information data has laid the cornerstone for the application of big data analysis. How to effectively mine data resources,…
Current multistage hydraulic fracturing operations in shale are costly, environmentally challenging and inefficient. Multistage hydraulic fracturing operations already represent close to 60% of the total drilling and completion cost for each shale…
Performance prediction is one of the important contents of oilfield development. It is also an important content affecting investment decision-making, especially for offshore oilfields with large investment. At present, most oilfields in China have…
Besides the rapid developments in the energy industry, there are substantial technological advances. The energy industry is calling for a strategic transformation of operation and business models through digital technologies and integrated data…
Our definition of 'The Big Data' is the ability of having all the data set at the point of decision-making.Several documented research shows that less than 5% of all the data acquired in the oil and gas industry areactually utilised. Despite these…
Based on the big data theory and data mining of gas pipeline failure history, the key factors determining the safety of pipeline system are found out, such as probability, function, time and prescribed conditions. Based on the reliability principle,…
When changes happen to big data analytics (BDA) applications in the Cloud at runtime, the affected BDA applications have to be re-deployed to accommodate the changes. Deciding the most suitable deployment is critical and complicated. Although there…
As the first decade of the US shale revolution continues, rod pump systems are still the prominent form of artificial lift. Technological advancements in diagnostic tools for rod pump systems, such as fluid level guns and dynamometers, have enabled…
Safety enhancement is the priority of every organization. Annually millions of dollars are spent to develop procedures and practices to diminish the health, safety and environmental disasters. Monitoring incidents and hazards and performing timely…
This paper focuses on increasing the efficiency of the E&P Companies in their extraction process with a new approach and methodology based on Big Data Analytics. This involves an approach in which the E & P companies could extract out the best of the…
Petroleum exploration activities demand the creation of lots of models to represent the uncertainties of a given reservoir, aiming to guide decision-making regarding exploration strategies. As part of these activities, a data assimilation process may…
Sisi and Nubi (SNB) fields are two adjacent primarily gas fields located 25 km offshore from the modern Mahakam delta These fields are complex from a reservoir management point of view with hundred thousands of Static & dynamic data, and continuously…
In this paper, an optimization method based on big data was proposed to improve the desulfurization selectivity and reduce the energy consumption of traditional acid gas sweetening technologies. At first, decision-making parameters which have…
Petroleum exploration and production processes typically generate enormous amounts of petro-Technical data using sub-surface and surface sensors. The acquisition, transferring, managing, and interpreting of these huge sensor data, as well as the…
Many methods have been proposed for leak detection in pipelines. The method based on the acoustic signals created by the leakage is a non-destructive method and has presented reliable results. However, applying such a method in noisy environments is…
In recent years, there has been a proliferation of massive subsurface data from instrumented wells. This places significant challenges on traditional production data analysis methods for extracting useful information, in support of reservoir…
In less than a decade, there has been a tremendous evolution in the various storage solutions used to contain wellsite data in the upstream oil and gas industry. Many organizations from wellsite data management providers to the oil and gas operators…
Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive.…
Establishing a Big Data Analytics environment for Drilling operations is impacted by many factors such as the nature of drilling operations that requires quick decision making and has a diversity of data sources. This paper goes over the process of…
As the first decade of the US shale revolution continues, rod pump systems are still the prominent form of artificial lift. Technological advancements in diagnostic tools for rod pump systems, such as fluid level guns and dynamometers, have enabled…
Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
Safety enhancement is the priority of every organization. Annually millions of dollars are spent to develop procedures and practices to diminish the health, safety and environmental disasters. Monitoring incidents and hazards and performing timely…
This paper focuses on increasing the efficiency of the E&P Companies in their extraction process with a new approach and methodology based on Big Data Analytics. This involves an approach in which the E & P companies could extract out the best of the…
The concept of digital transformation is based on two principles: data drivenexploiting every bit of data sourceand user focused. The objective is not only to consolidate data from multiple systems, but to apply an analytics approach to extract…
Current multistage hydraulic fracturing operations in shale are costly, environmentally challenging and inefficient. Multistage hydraulic fracturing operations already represent close to 60% of the total drilling and completion cost for each shale…
Petroleum exploration activities demand the creation of lots of models to represent the uncertainties of a given reservoir, aiming to guide decision-making regarding exploration strategies. As part of these activities, a data assimilation process may…
Our research aims to analyze how the uncertainties and risks of the overseas oil & gas investment environment change over time and reveal the specific occurrence probabilities of risk on different levels. In the process of long-drawn overseas oil &…
Problem Statement: Due to the availability of large quantities of real-time data, many operators are faced with the challenge of extracting meaningful information from it. In many cases, analysis of the data, the updating of models for Wells,…