The Limitation of Reservoir Saturation Logging Tool in a Case of a Deeper Reservoir Flow into a Shallower Reservoir Within the Same Wellbore

2021 ◽  
Author(s):  
P. Merit Ekeregbe
Keyword(s):  
Decision Making ◽  
Flow Condition ◽  
Oil And Gas ◽  
Static Condition ◽  
Oil And Gas Industry ◽  
Well Performance ◽  
Liquid Loading ◽  
Critical Rate ◽  
Logging Tool ◽  
Historical Production

Abstract Saturation logging tool is one key tool that has been successfully used in the Oil and Gas Industry. As important as the tool is, it should not be mistaken for a decision tool, rather it is a tool that aids decision making. Because the tool aids decision making, the decision process must be undertaken by interdisciplinary team of Engineers with historical knowledge of the tool and the performance trend of the candidate well and reservoir. No expertise is superior to historical data of well and reservoir performance because the duo follows physics and any deviation from it is attributable to a misnomer. The decision to re-enter a well for re-perforation or workover must be supported by historical production and reasonable science which here means that trends are sustained on continuous physics and not abrupt pulses. Any interpretation arising from saturation logging tools without subjecting same to reasonable science could result in wrong action. This paper is providing a methodology to enhance thorough screening of candidates for saturation logging operations. First is to determine if the candidate well is multilevel and historical production above critical gas rate before shut-in to screen-out liquid loading consideration. If any level is plugged below any producing level, investigate for micro-annuli leakage. All historical liquid loading wells should be flowed at rate above critical rate and logged at flow condition. Static condition logging is only good for non-liquid loading wells. The use of any tool and its interpretation must be subjective and there comes the clash between the experienced Sales Engineer and the Production/Reservoir Engineer with the historical evidence. A simple historical trending and analysis results of API gravity and BS&W were used in the failed plug case-study. Further successful investigation was done and the results of the well performance afterwards negated the interpretation arising from the saturation tool which saw the reservoir sand flushed. The lesson learnt from the well logging and interpretation shows that when a well is under any form of liquid loading, interpretation must be subjective with reasonable science and historical production trend is critical. It is recommended that when a well is under historical liquid loading rate, until the rate above the critical rate is determined, no logging should be done and when done, logging should be at flow condition and the interpretation subject to reasonable system physics.

Prediction of Liquid Loading in Gas Condensate and Volatile Oil Wells for Unconventional Reservoirs

2020 ◽  
Author(s):  
Reem Alsadoun ◽  
Mohammad Al Momen ◽  
Hongtao Luo
Keyword(s):  
Production Efficiency ◽  
Oil And Gas ◽  
Theoretical Calculations ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Economic Losses ◽  
Well Performance ◽  
Liquid Loading ◽  
Critical Rate ◽  
Correlation Models

Abstract All producing wells experience reservoir pressure depletion which will ultimately cause production to cease. However, the accumulation of wellbore liquid known as liquid loading can reduce production at a faster rate bringing forward the end of well life. In theory, there are many works written on liquid loading in unconventional wells however, these assumptions are challenged when implemented in the field. The aim of this paper is to investigate the relationship between empirical and mechanistic methods used to determine liquid loading critical rates for volatile oil and gas condensate wells, improving liquid loading forecast workflow for future wells. The study was carried on a wide Pressure, Volume, and Temperature (PVT) window with varying compositions ranging from gas condensate to volatile oils. Wells with liquid loading exhibit sharp drops and fluctuations in production. Due to the wide variation in composition however, correlations used must be varied whilst accounting for both composition and horizontal configuration of the well. Using Nodal Analysis methods, Inflow Performance Relationships (IPR) and Vertical Lift Profile (VLP) curves were created from different correlation models fitted for multiple wells selected for this study to optimize well performance. By combining theoretical analysis and field practices for estimating liquid loading critical rate, the appropriate workflow was determined for the volatile oil and gas condensate wells. When comparing the critical rate for liquid loading calculated from theoretical methods against actual rates seen in the field, an inconsistency was observed between the two values for several wells. By establishing a relationship between field estimate and theoretical calculations, liquid loading was forecasted with greater certainty for varying PVT windows. When the liquid loading rate is determined earlier on, the production efficiency can be improved by deploying unloading measures, increasing the well’s producing life, and ultimately alleviating economic losses. By investigating, we were able to establish a suitable process to predict liquid loading critical rates for volatile oil and gas condensate wells. This workflow can be utilized by production engineers to arrange for liquid loading mitigation increasing well life and improving well economics.

A Novel Corrosion Monitoring and Prediction System Utilizing Advanced Artificial Intelligence

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Waleed Dokhon ◽  
Fahmi Aulia ◽  
Mohanad Fahmi
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Salt Water ◽  
Oil And Gas Industry ◽  
Training Dataset ◽  
Metal Loss ◽  
Corrosion Monitoring ◽  
Prediction System ◽  
Well Performance ◽  
Data Driven Approach

Abstract Corrosion in pipes is a major challenge for the oil and gas industry as the metal loss of the pipe, as well as solid buildup in the pipe, may lead to an impediment of flow assurance or may lead to hindering well performance. Therefore, managing well integrity by stringent monitoring and predicting corrosion of the well is quintessential for maximizing the productive life of the wells and minimizing the risk of well control issues, which subsequently minimizing cost related to corrosion log allocation and workovers. We present a novel supervised learning method for a corrosion monitoring and prediction system in real time. The system analyzes in real time various parameters of major causes of corrosion such as salt water, hydrogen sulfide, CO2, well age, fluid rate, metal losses, and other parameters. The data are preprocessed with a filter to remove outliers and inconsistencies in the data. The filter cross-correlates the various parameters to determine the input weights for the deep learning classification techniques. The wells are classified in terms of their need for a workover, then by the framework based on the data, utilizing a two-dimensional segmentation approach for the severity as well as risk for each well. The framework was trialed on a probabilistically determined large dataset of a group of wells with an assumed metal loss. The framework was first trained on the training dataset, and then subsequently evaluated on a different test well set. The training results were robust with a strong ability to estimate metal losses and corrosion classification. Segmentation on the test wells outlined strong segmentation capabilities, while facing challenges in the segmentation when the quantified risk for a well is medium. The novel framework presents a data-driven approach to the fast and efficient characterization of wells as potential candidates for corrosion logs and workover. The framework can be easily expanded with new well data for improving classification.

Failure Mechanisms of the Wellbore Mechanical Barrier Systems: Implications for Well Integrity

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Shawgi Ahmed ◽  
Saeed Salehi
Keyword(s):  
Oil And Gas ◽  
Failure Mechanisms ◽  
Oil And Gas Industry ◽  
Well Performance ◽  
Acidic Gases ◽  
Well Integrity ◽  
Elastomeric Materials ◽  
Main Motive ◽  
Geothermal Wells ◽  
Mechanical Barrier

Abstract Energy sustainability is the main motive behind the evolution of the concept of well integrity in the oil and gas industry. The concept of well integrity adopts technical, operational, environmental, organizational, and safety measurements to secure the energy supply throughout the life of the well. Technically, a high quality well performance can be maintained by establishing robust barrier systems that are responsible for preventing, controlling, and mitigating potential risks that could arise during the well life cycle. A barrier system is conventionally nested from one or multiple elements that act individually or collectively to scaffold the well integrity. The protection layers in a wellbore can be lost if the integrity of the barrier system is compromised according to the failure of one or all of its elements. Failure can be triggered by technical or non-technical factors. In this study, technical aspects that drive barrier failure mechanisms have given more emphasis. The failure mechanisms of the key mechanical barrier systems, such as casing strings, cement, diverters, blowout preventers (BOPs), production stream valves, and seal assemblies, have been thoroughly investigated. In this study, a comprehensive review of barriers failure mechanisms has been conducted to identify the roots of failures and to outline some of the essential safety measures adopted to avoid the loss of well control. The major findings of this paper revealed that well barrier systems are highly susceptible to failure in unconventional reservoirs, deep and ultra-deep offshore wells, and geothermal wells. The predominant failures identified are casing collapse resulting from cyclic loads, cement percolation by gas migration, cement carking by hoop stress, BOPs wear and tear promoted by frequent tests, and elastomeric materials disintegration caused by acidic gases. Considering these failure mechanisms while designing a wellbore can help the engineers improve the construction quality. In addition, it can assist the operation and maintenance crews in optimizing safe operation boundaries.

A Novel Methodology for Optimal Design of Compressor Plants Using Probabilistic Plant Design

2013 ◽  
Vol 135 (11) ◽  
Author(s):  
Rainer Kurz ◽  
J. Michael Thorp ◽  
Erik G. Zentmyer ◽  
Klaus Brun
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Process Conditions ◽  
Plant Design ◽  
Well Performance ◽  
Worst Case ◽  
Gas Industry ◽  
Machine Performance ◽  
Equipment Sizing

Equipment sizing decisions in the oil and gas industry often have to be made based on incomplete data. Often, the exact process conditions are based on numerous assumptions about well performance, market conditions, environmental conditions, and others. Since the ultimate goal is to meet production commitments, the traditional method of addressing this is to use worst case conditions and often adding margins onto these. This will invariably lead to plants that are oversized, in some instances, by large margins. In reality, the operating conditions are very rarely the assumed worst case conditions, however, they are usually more benign most of the time. Plants designed based on worst case conditions, once in operation, will, therefore, usually not operate under optimum conditions, have reduced flexibility, and therefore cause both higher capital and operating expenses. The authors outline a new probabilistic methodology that provides a framework for more intelligent process-machine designs. A standardized framework using a Monte Carlo simulation and risk analysis is presented that more accurately defines process uncertainty and its impact on machine performance. Case studies are presented that highlight the methodology as applied to critical turbomachinery.

DECISION TYPE—A KEY TO REALISING THE POTENTIAL OF DECISION MAKING UNDER UNCERTAINTY

2007 ◽  
Vol 47 (1) ◽  
pp. 309 ◽  
Author(s):  
S.I. Mackie ◽  
S.H. Begg ◽  
C. Smith ◽  
M.B. Welsh
Keyword(s):  
Decision Making ◽  
Real World ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Decision Making Under Uncertainty ◽  
Gas Industry ◽  
The Past ◽  
Decision Outcomes ◽  
Decision Type ◽  
Definition Of

Business underperformance in the upstream oil and gas industry, and the failure of many decisions to return expected results, has led to a growing interest over the past few years in understanding the impacts of decisionmaking tools and processes and their relationship to decision outcomes. A primary observation is that different decision types require different decision-making approaches to achieve optimal outcomes.Optimal decision making relies on understanding the types of decisions being made and tailoring the type of decision with the appropriate tools and processes. Yet the industry lacks both a definition of decision types and any guidelines as to what tools and processes should be used for what decisions types. We argue that maximising the chances of a good outcome in real-world decisions requires the implementation of such tailoring.

Sustainable partnerships: the art of high-performing alliances and joint ventures

2016 ◽  
Vol 56 (2) ◽  
pp. 558
Author(s):  
Amita Riksen ◽  
Nick Chipman
Keyword(s):  
Decision Making ◽  
Strategic Alliances ◽  
Joint Ventures ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Business Environment ◽  
Strategic Objectives ◽  
High Performing ◽  
Industry Response

In the increasingly transparent, real-time, digital business environment, the degree of collaboration required to succeed is rapidly expanding. Interdependencies created among diverse market participants, prospective partners and stakeholders is dramatically altering who actively participates in the oil and gas industry and how much influence they can yield. An industry deeply premised on technical innovation and excellence must evolve to broaden the value proposition and address the complex, expanded stakeholder groups. Traditional value drivers need to be extended to effectively leveragemulti-party joint ventures (JVs) to address the principles of license to operate and deliver the required capabilities. PwC hypothesises that risk-averse, technical, legal and quantitative biases drive joint venturing agreements to narrow obligations and sub-optimal outcomes. This is because narrow agreements ignore the behavioural, organisational and critical relationship-driven outcomes in contracting, venturing and alliance configurations. By widening the lens of JV agreements and strategic alliances, the authors look briefly at real case studies and undertake critical observations of the emerging industry behaviour, in identifying the following range of factors industry participants need to confront: the power and agility of social media driving industry response; the role of subjective, human factors in realising strategic objectives; the perceived rights of JV parties as the reality; the role of emotion in decision making and misalignments of culture/style/behaviours among stakeholders; the balance of diversity versus control requirements in governance management; the enablers for co-creating, high-performing ventures and contracting for co-operation alongside risk management; using the letter of the contract to facilitate rather than dictate behaviour; and, the power of influence to enable decision making. The shared experiences of the authors identify an attribution framework underpinning the contractual frame and extends into the effective planning and execution traits of high-performing, co-operative JVs.

scholarly journals Group Collaboration And Group Decision Making Information Technologies In Petroleum Industry

2005 ◽  
Vol 9 (3) ◽  
pp. 47-52
Author(s):  
Alpana M. Desai
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Management Practices ◽  
Business Processes ◽  
Oil And Gas ◽  
Group Decision ◽  
Petroleum Industry ◽  
Oil Industry ◽  
Oil And Gas Industry ◽  
Oil Companies

The technical management of important natural resources such as oil and gas resources is a challenging responsibility that faces oil companies. The increasing global demand for oil and gas coupled with declining oil and gas reserves has forced the oil industry to make significant changes in its business processes. Major oil companies have exploration and production operations that span several continents. Massive amount of data that is generated at all levels in an oil company has to be stored, analyzed and disseminated. In this paper, the changes in the management practices and business processes in the oil industry are traced over the past several decades. The use and application of information technology as change agents is also explored and evaluated. In particular, this paper focuses on the role of visualization centers in the oil and gas industry in revolutionizing effective group decision making that has enabled teams to be more productive, innovative, and outcome-focused.

Sign in / Sign up

Export Citation Format

Share Document