Artificial Neural Network as a Method for Pore Pressure Prediction throughout the Field

2021 ◽  
Author(s):  
Danila Mylnikov ◽  
Viktor Nazdrachev ◽  
Evgeniy Korelskiy ◽  
Yuriy Petrakov ◽  
Alexey Sobolev
Keyword(s):  
Neural Network ◽  
Pore Pressure ◽  
Oil And Gas ◽  
Model Building ◽  
Traditional Approach ◽  
Oil And Gas Industry ◽  
Model Construction ◽  
Analytical Models ◽  
Geomechanical Model ◽  
Field Development

Abstract Geomechanical model construction is an essential part of field development processes planning. Building a correct pore pressure model is one of the key tasks within the process of geomechanical model construction. The traditional approach to pore pressure modeling in oil and gas industry is based on the empirical analytical models usage. This approach has a number of disadvantages, which often lead to the constructed pore pressure model to be incorrect. The authors highlight two most significant disadvantages of the traditional approach: 1) a priori discrepancy between the empirical model and fundamental physical laws; 2) the impossibility of selecting such a combination of parameters of the standard analytical model, for which the resulting pressure corresponds to the entire set of actual field data (pore pressure measurements). This paper proposes a methodology for assessing the pore pressure distribution across the field, based on the usage of neural network technology. This approach potentially eliminates both of the above disadvantages from the pore pressure model building.

Boosting Algorithm Choice in Predictive Machine Learning Models for Fracturing Applications

2021 ◽  
Author(s):  
Abdul Muqtadir Khan
Keyword(s):  
Machine Learning ◽  
Data Science ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Injection Rate ◽  
Model Construction ◽  
Gradient Boosting ◽  
Light Gradient ◽  
Fracture Damage ◽  
Boosting Technique

Abstract With the advancement in machine learning (ML) applications, some recent research has been conducted to optimize fracturing treatments. There are a variety of models available using various objective functions for optimization and different mathematical techniques. There is a need to extend the ML techniques to optimize the choice of algorithm. For fracturing treatment design, the literature for comparative algorithm performance is sparse. The research predominantly shows that compared to the most commonly used regressors and classifiers, some sort of boosting technique consistently outperforms on model testing and prediction accuracy. A database was constructed for a heterogeneous reservoir. Four widely used boosting algorithms were used on the database to predict the design only from the output of a short injection/falloff test. Feature importance analysis was done on eight output parameters from the falloff analysis, and six were finalized for the model construction. The outputs selected for prediction were fracturing fluid efficiency, proppant mass, maximum proppant concentration, and injection rate. Extreme gradient boost (XGBoost), categorical boost (CatBoost), adaptive boost (AdaBoost), and light gradient boosting machine (LGBM) were the algorithms finalized for the comparative study. The sensitivity was done for a different number of classes (four, five, and six) to establish a balance between accuracy and prediction granularity. The results showed that the best algorithm choice was between XGBoost and CatBoost for the predicted parameters under certain model construction conditions. The accuracy for all outputs for the holdout sets varied between 80 and 92%, showing robust significance for a wider utilization of these models. Data science has contributed to various oil and gas industry domains and has tremendous applications in the stimulation domain. The research and review conducted in this paper add a valuable resource for the user to build digital databases and use the appropriate algorithm without much trial and error. Implementing this model reduced the complexity of the proppant fracturing treatment redesign process, enhanced operational efficiency, and reduced fracture damage by eliminating minifrac steps with crosslinked gel.

Challenges in Hydrate Plug Prevention in Pipelines Seen Over the Lifetime of a Field

2009 ◽  
Author(s):  
Casper Hadsbjerg ◽  
Kristian Krejbjerg
Keyword(s):  
Oil And Gas ◽  
Formation Rate ◽  
Hydrate Formation ◽  
Extended Period ◽  
Oil And Gas Industry ◽  
High Water ◽  
Point Of View ◽  
Field Development ◽  
Hydrate Plug ◽  
Subsea Pipelines

When the oil and gas industry explores subsea resources in remote areas and at high water depths, it is important to have advanced simulation tools available in order to assess the risks associated with these expensive projects. A major issue is whether hydrates will form when the hydrocarbons are transported to shore in subsea pipelines, since the formation of a hydrate plug might shut down a pipeline for an extended period of time, leading to severe losses. The industry practices a conservative approach to hydrate plug prevention, which is the addition of inhibitors to ensure that hydrates cannot form under pipeline pressure and temperature conditions. The addition of inhibitors to subsea pipelines is environmentally unfriendly and also a very costly procedure. Recent efforts has therefore focused on developing models for the hydrate formation rate (hydrate kinetics models), which can help determine how fast hydrates might form a plug in a pipeline, and whether the amount of inhibitor can be reduced without increasing the risk of hydrate plug formation. The main variables determining whether hydrate plugs form in a pipeline are: 1) the ratio of hydrocarbons to water, 2) the composition of the hydrocarbons, 3) the flowrates/flow regimes in the pipeline, 4) the amount of inhibitor in the system. Over the lifetime of a field, all 4 variables will change, and so will the challenge of hydrate plug prevention. This paper will examine the prevention of hydrate plugs in a pipeline, seen from a hydrate kinetics point of view. Different scenarios that can occur over the lifetime of a field will be investigated. Exemplified through a subsea field development, a pipeline simulator that considers hydrate formation in a pipeline is used to carry out a study to shed light on the most important issues to consider as conditions change. The information gained from this study can be used to cut down on inhibitor dosage, or possibly completely remove the need for inhibitor.

Utilizing Pseudo Well Connections to Simulate Multi-Stage Hydraulic Fracturing - Example Based On the Study of a Tight Gas Asset

2021 ◽  
Author(s):  
Aamir Lokhandwala ◽  
Vaibhav Joshi ◽  
Ankit Dutt
Keyword(s):  
Hydraulic Fracturing ◽  
Oil And Gas ◽  
Flow Simulation ◽  
Oil And Gas Industry ◽  
Development Plan ◽  
Hydraulic Fractures ◽  
Tight Gas ◽  
Gas Field ◽  
Field Development ◽  
Fracture Modeling

Abstract Hydraulic fracturing is a widespread well stimulation treatment in the oil and gas industry. It is particularly prevalent in shale gas fields, where virtually all production can be attributed to the practice of fracturing. It is also used in the context of tight oil and gas reservoirs, for example in deep-water scenarios where the cost of drilling and completion is very high; well productivity, which is dictated by hydraulic fractures, is vital. The correct modeling in reservoir simulation can be critical in such settings because hydraulic fracturing can dramatically change the flow dynamics of a reservoir. What presents a challenge in flow simulation due to hydraulic fractures is that they introduce effects that operate on a different length and time scale than the usual dynamics of a reservoir. Capturing these effects and utilizing them to advantage can be critical for any operator in context of a field development plan for any unconventional or tight field. This paper focuses on a study that was undertaken to compare different methods of simulating hydraulic fractures to formulate a field development plan for a tight gas field. To maintaing the confidentiality of data and to showcase only the technical aspect of the workflow, we will refer to the asset as Field A in subsequent sections of this paper. Field A is a low permeability (0.01md-0.1md), tight (8% to 12% porosity) gas-condensate (API ~51deg and CGR~65 stb/mmscf) reservoir at ~3000m depth. Being structurally complex, it has a large number of erosional features and pinch-outs. The study involved comparing analytical fracture modeling, explicit modeling using local grid refinements, tartan gridding, pseudo-well connection approach and full-field unconventional fracture modeling. The result of the study was to use, for the first time for Field A, a system of generating pseudo well connections to simulate hydraulic fractures. The approach was found to be efficient both terms of replicating field data for a 10 year period while drastically reducing simulation runtime for the subsequent 10 year-period too. It helped the subsurface team to test multiple scenarios in a limited time-frame leading to improved project management.

Challenges of Developing Marginal Fields in the Current Climate of Oil and Gas Industry

2021 ◽  
Author(s):  
Amina Danmadami ◽  
Ibiye Iyalla ◽  
Gbenga Oluyemi ◽  
Jesse Andrawus
Keyword(s):  
Oil And Gas ◽  
Dynamic Environment ◽  
Poor Performance ◽  
Oil And Gas Industry ◽  
Economic Benefits ◽  
Gas Industry ◽  
Field Development ◽  
Quality Technology ◽  
Indigenous Participation ◽  
Marginal Field

Abstract Marginal field development has gained relevance in oil producing countries because of the huge potential economic benefits it offers. The Federal Government of Nigeria commenced a Marginal Fields program in 2001 as part of her policy to improve the nation’s strategic oil and gas reserves and promote indigenous participation in the upstream sector. Twenty years after the award of marginal fields to indigenous companies to develop, 50% have developed and in production, 13% have made some progress with their acquisition while 37% remain undeveloped. The poor performance of the marginal field operators is due to certain challenges which have impeded their progress. A review of challenges of developing marginal fields in the current industry climate was conducted on marginal fields in Nigeria to identify keys issues. These were identified as: funding, technical, and public policy. Considering the complex, competitive and dynamic environment in which these oil and gas companies operate, with competition from renewables, pressure to reduce carbon footprint, low oil price and investors expectation of a good return, companies must maintain tight financial plan, minimize emissions from their operations and focus on efficiency through innovation. The study identifies the need for a decision-making approach that takes into consideration multi criteria such as cost, regulation, quality, technology, security, stakeholders, safety and environment, as important criteria based on which to evaluate the selection of appropriate development option for marginal fields.

Three-Phase Flow Profile Determination of A Horizontal Well in Offshore by Tracer Technology

2021 ◽  
Author(s):  
Alexander Katashov ◽  
Igor Novikov ◽  
Evgeny Malyavko ◽  
Nadir Husein
Keyword(s):  
Oil And Gas ◽  
Horizontal Wells ◽  
Oil And Gas Industry ◽  
World Market ◽  
Dynamic Mode ◽  
Flow Profile ◽  
Offshore Platforms ◽  
Field Development ◽  
Coiled Tubing ◽  
Three Phase

Abstract Over the past few years, the oil and gas industry has faced a situation of high fluctuations in hydrocarbon prices on the world market. In addition, the trend for the depletion of traditional hydrocarbon reservoirs and the search for new effective solutions for the management and control of field development using horizontal and multilateral wells is still relevant. The most common method for horizontal wells testing is production logging tools (PLT) on coiled tubing (CT) or downhole tractor, which is associated with HSE risks and high cost, especially on offshore platforms, which limits the widespread use of this technology. The solution without such risks is the method of marker well monitoring, which allows obtaining information about the profile and composition of the inflow in a dynamic mode in horizontal wells without well intervention. There are several types of tracer (marker) carriers and today we will consider an approach to placing marker monitoring systems as part of a completion for three-phase oil, water and gas monitoring.

Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

2021 ◽  
pp. 154-184
Author(s):  
Sorin Alexandru Gheorghiu ◽  
Cătălin Popescu
Keyword(s):  
Business Performance ◽  
Oil And Gas ◽  
Water Injection ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Gas Industry ◽  
Field Development ◽  
Drilling Rig ◽  
Oil Field Development ◽  
Oil Gas

The present economic model is intended to provide an example of how to take into consideration risks and uncertainties in the case of a field that is developed with water injection. The risks and uncertainties are related, on one hand to field operations (drilling time, delays due to drilling problems, rig failures and materials supply, electric submersible pump [ESP] installations failures with the consequences of losing the well), and on the other hand, the second set of uncertainties are related to costs (operational expenditures-OPEX and capital expenditures-CAPEX, daily drilling rig costs), prices (oil, gas, separation, and water injection preparation), production profiles, and discount factor. All the calculations are probabilistic. The authors are intending to provide a comprehensive solution for assessing the business performance of an oil field development.

Financing Requirements for the Oil and Gas Industry - North America

1988 ◽  
Vol 6 (4-5) ◽  
pp. 317-322
Author(s):  
A.F. Grove
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Field ◽  
Gas Industry ◽  
Field Development ◽  
Energy Company ◽  
Corporate Credit ◽  
Oil And Gas Field ◽  
Good Energy ◽  
Business Acumen

The characteristics of good energy company borrowers are strong management, integrity, diversification, flexibility, a sound financial basis and business acumen. Acceptable reasons for borrowing include requirements for working capital, plant expansion, modernisation, oil and gas field development and the manufacturing of oil tools and related products. Security for loans is based on the company's reserves, the duration of the debt and priority over other indebtedness. Most loans are evaluated on the grounds of general corporate credit, that is, the overall credit standing of the borrower.

Wheel Box Test Aeromechanical Verification of New First Stage Bucket With Integrated Cover Plates for MS5002 GT

2019 ◽  
Author(s):  
Marco Mariottini ◽  
Nicola Pieroni ◽  
Pietro Bertini ◽  
Beniamino Pacifici ◽  
Alessandro Giorgetti
Keyword(s):  
Gas Turbine ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Response Assessment ◽  
Operating Conditions ◽  
Analytical Models ◽  
Gas Industry ◽  
Improved Performance ◽  
Cover Plates

Abstract In the oil and gas industry, manufacturers are continuously engaged in providing machines with improved performance, reliability and availability. First Stage Bucket is one of the most critical gas turbine components, bearing the brunt of very severe operating conditions in terms of high temperature and stresses; aeromechanic behavior is a key characteristic to be checked, to assure the absence of resonances that can lead to damage. Aim of this paper is to introduce a method for aeromechanical verification applied to the new First Stage Bucket for heavy duty MS5002 gas turbine with integrated cover plates. This target is achieved through a significantly cheaper and streamlined test (a rotating test bench facility, formally Wheel Box Test) in place of a full engine test. Scope of Wheel Box Test is the aeromechanical characterization for both Baseline and New bucket, in addition to the validation of the analytical models developed. Wheel Box Test is focused on the acquisition and visualization of dynamic data, simulating different forcing frequencies, and the measurement of natural frequencies, compared with the expected results. Moreover, a Finite Elements Model (FEM) tuning for frequency prediction is performed. Finally, the characterization of different types of dampers in terms of impact on frequencies and damping effect is carried out. Therefore, in line with response assessment and damping levels estimation, the most suitable damper is selected. The proposed approach could be extended for other machine models and for mechanical audits.

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