Iran

Ultimate Shear Strength of Pitted Plates with Crack Using Finite Element Method

Ranji, Ahmad Rahbar (Amirkabir University of Technology, Tehran / University of Windsor, Windsor) | Maghsodi, Nima (Amirkabir University of Technology, Tehran) | Alirezaee, Shahpour (University of Windsor, Windsor)

OnePetroMay, 2023

_ Ultimate strength of thin steel plates was studied under shear loading when pitting corrosion and cracking occur simultaneously. Nonlinear finite element method was used and the effects of different geometrical parameters, such as crack position, crack length, pit depth, pit diameter, number of the pits, and the inclination angle of the crack, were investigated. It was found that the degree of the pitting (DOP) significantly reduces the ultimate shear strength of the pitted plates when the corrosion is low. For high amount of corrosion, the reduction of the ultimate shear strength remains the same regardless of the amount of the DOP. In plates with short cracks, the crack length has no influence on the reduction of the ultimate shear strength. Also, it was found that the position of the crack is more effective than the length of the crack on the reduction of the ultimate shear strength of the cracked plates. In the cracked-pitted plates, there was no interaction between crack and pit for extremes value of DOP. For low value of DOP, the ultimate shear strength of the cracked-pitted plate was the same as the cracked plate, and for large value of DOP, it is the same as pitted plate. Introduction According to a study performed between 2002 and 2008 by American Bureau of Shipping (ABS) (“Review of Current Practices of Fracture” 2012), majority of reported fractures of the ships were structural failures, such as weld defect, buckling, fracture, and cracking. Cracks and corrosion are two more common defects, which are the main reasons of the failure of the aged steel structures. Plates and stiffened plates are the main structural elements in many structures, including airplanes, bridges, offshore structures, and ships. Ultimate strength evaluation of these structural elements is crucial for rational design of structures, such as Load Resistance Factor Design (LRFD) methods in civil engineering and Ultimate Strength (UTS) evaluation in ship structure. Many studies are carried out to evaluate ultimate strength of intact and damaged plates/ stiffened plates under in-plane compressive stress. Ranji (2012) studied ultimate strength of plate with general corrosion under in-plane compression. He proposed a spectrum for random generation of corroded surface and ultimate strength of corroded plate was evaluated using computer code ANSYS. Ranji and Zarookian (2015) analyzed ultimate strength of cracked stiffened plates with cracks having different stiffeners numerically.

OnePetro

doi: 10.5957/JSPD.02220008

SNAME

SNAME-JSPD-02220008

Journal of Ship Production and Design

Country:

North America > United States (0.34)
Asia > Middle East > Iran (0.28)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Completion > Well Integrity > Subsurface corrosion (tubing, casing, completion equipment, conductor) (1.00)
Facilities Design, Construction and Operation > Pipelines, Flowlines and Risers > Materials and corrosion (1.00)

Technology: Information Technology > Modeling & Simulation (0.61)

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Estimation of Shear Wave Velocity Using Empirical, MLR, and GEP Techniques-Case Study: Kharg Island Offshore Oilfield

Zamani Ahmad Mahmoudi, Mohammad (AGH University of Science and Technology) | Khalilidermani, Mitra (AGH University of Science and Technology) | Knez, Dariusz (AGH University of Science and Technology)

OnePetroMay, 2023

Abstract Determination of the shear wave velocity, Vs, is an integral part in creation of reservoir geomechanical models. This parameter together with the compressional wave velocity and rock density are utilized to calculate the dynamic elastic moduli of the subsurface formations. In well logging, the Vs can be directly measured through the Dipole Shear Sonic Imager (DSI) logs which need special requirements and technical considerations. Therefore, many researchers have strived to develop cost-effective accurate methods for Vs estimation in the oil/gas fields. The Kharg Island offshore oilfields, located in the Persian Gulf, consist of a giant limestone reservoir called Asmari formation. In the past, numerous studies were conducted to develop mathematical relations for Vs prediction in the Asmari reservoir; however those relations were not capable of estimating the Vs values correctly. In this research, the well logging data related to a vertical offshore well was utilized to develop three mathematical relations for Vs estimation in the Asmari formation. To do this, linear regression (LR), Multivariate Regression (MLR), and Gene Expression Programing (GEP) methods were applied. Moreover, the accuracy of those relations was compared with some available empirical correlations for Vs prediction in limestone rocks. Comparing the results of those data-driven equations with the empirical equations illustrated that the results of the GEP method are more accurate than other equations. Moreover, the Pickett empirical correlation was found to be more suitable than other empirical correlations for Vs estimation in the Asmari reservoir. The methodology applied in this research is a reliable procedure to estimate the Vs in the study area as well as other geologically similar oil reservoirs. Such an application leads to generation of robust geomechanical models increasing the project success and oilfield development progression.

OnePetro

doi: 10.4043/32388-MS

OTC

OTC-32388-MS

Offshore Technology Conference

Country:

North America > United States (1.00)
Asia > Middle East > Iran (0.47)
Asia > Middle East > Saudi Arabia > Arabian Gulf (0.25)

Genre: Research Report (0.47)

Geologic Time: Phanerozoic (0.46)

Geophysics:

Geophysics > Seismic Surveying > Seismic Processing (0.63)
Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.63)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Treachery Formation (0.99)
Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Mt. Goodwin Formation (0.99)
Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Keyling Formation (0.99)
(18 more...)

SPE Disciplines:

Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)

Technology:

Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Regression (1.00)
Information Technology > Artificial Intelligence > Machine Learning > Evolutionary Systems (0.93)

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A New Approach of Petrophysical Rock Typing (PRT) for Carbonate Reservoir Using KNN Based on Conventional Wireline Data and Core Analysis Data

Nie, Xiang Bin (Kuwait Energy Basra Limited) | Wang, An (Kuwait Energy Basra Limited) | Hao, Jianfei (Kuwait Energy Basra Limited)

OnePetroMarch, 2023

Abstract For reservoir simulation, one of the most important part of reservoir characterization is rock typing, where rock quality is evaluated and estimated for any simulation grid and OOIP (original oil in place) is calculated based on average petrophysical parameters for any layer. To allocate different rock types to simulation grids, rock types should be assigned according to ranges of parameters that differentiate different rock types. Based on the experience in carbonate reservoirs of XXXX oilfield and other oilfields, irreducible water saturation (Swi) is a critical differentiation parameter for rock typing, although it can be difficult and expensive to evaluate. In oil zones, water saturation from log data is assumed to be the irreducible water saturation. The problem arises in transition zone and water zone, where water saturation from log data is not equal to the irreducible water saturation of that rock. KNN(K-Nearest Neighbor) is an effective machine learning method for classification and regression in many industries including geo-science. Models can be trained and predict irreducible water saturation from the traditional logs such as GR, Density, Neutron, Sonic using KNN and other Machine Learning methods using labelled data from oil zones. Randomly selected 50% of the dataset was used for training and other 50% was used as testing dataset to be predicted. The prediction precision of KNN method can reach the minimum 92% line for all 25 wells studied and is most robust compared to other methods such as Random Forest and SVM. The trained model was used to predict all the rock types in the reservoir and was confirmed in wells with core data and other advanced measurements data. A new approach of petrophysical rock typing (PRT) for carbonate reservoir using KNN based on traditional wireline data and core analysis data is studied and the results show it can solve the PRT problems in carbonate reservoir simulation without acquiring extra data and additional cost. A new workflow was established to process wireline data and provide the PRT results based on wireline data for every newly drilled well on top of traditional "Porosity-Permeability-Saturation" petrophysical evaluation results. This paper presents the methodology, workflow, results, verification, as well as appropriate application scenarios of this new approach. Considering the requirements of the data input and the workflow of the approach, it could be applied widely in similar carbonate reservoirs.

OnePetro

doi: 10.2118/214200-MS

SPE

SPE-214200-MS

Gas & Oil Technology Showcase and Conference

Country: Asia > Middle East > Iran (0.28)

Genre:

Research Report > Experimental Study (1.00)
Overview > Innovation (0.82)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places: Asia > Middle East > Iran > Khuzestan > Zagros Basin > Aghajari Field (0.99)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
Reservoir Description and Dynamics > Reservoir Characterization (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
(2 more...)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Nearest Neighbor Methods (0.35)

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Essential Ingredients of Effective Project Management: A Case Study of Project Execution in the South Pars Mega-Projects

Daneshkhah, Vahid (Dana Energy Company) | Younesi, Gholamreza (Dana Energy Company) | Karbalaee Akbari, Meisam (Dana Energy Company) | Daneshkhah, Hamed (Dana Energy Company)

OnePetroMarch, 2023

Abstract During the past decades hundreds of wells have been constructed in the giant South Pars gas field with different approaches and methodologies leading to diverse outcomes and results. Interestingly enough there have been many operators in the field with distinct performances yet by deploying the same vendors and service providers held in common. By considering that it is statistically proven that the larger the project budget, there are higher chances for failure, effective tailoring of methodologies in large scale mega-projects would be crucial and decisive. In many cases failures are a consequence of simply applying methodologies already experienced in small scale projects on complex and sophisticated projects with a variety of influential factors and a huge network of stakeholders. The study has provided an insight on how effective approaches in project management or conversely mismanagement could play as the main rout cause in a chain of events corresponding to either saved time or Non-Productive Times in well construction operations by presenting real cases elaborated in detail. Cases show how failure in collecting requirements and recognizing the interdependencies among each necessity in the early stages of the project and subsequently overlooking the related cost, time and risks could cause massive cumulative financial loss. Additionally, failure to recognize wise investments in vendors and service providers as the 1-10-100 rule which explains how failure to take notice of one initial investment escalates the financial loss exponentially would have staggering consequences. The current paper explains how being proactive in an extensive planning phase could ease the execution stage as a great investment in time spent. From a human resource perspective, it has been demonstrated that how the ability and skills of the project team e.g. effective communication in complex networks with multiple reporting relationships and data-driven decisions by statistics could prevent cognitive biases and errors in decision making. Furthermore, powerful alignments come from shared and common motivations and morale for all engaged parties and the supply chain being service providers, rig contractors or the field operator and there should be an answer to the question, what's in it for me when asked by each of these parties. Overall the study presents real cases and lessons learned showing how the main rout causes of Non-Productive Times could go back deeply to ineffective project approaches from a project management perspective in a system dynamic chain of events rather than to just address the emerged symptoms of failure in drilling operation.

OnePetro

doi: 10.2118/214032-MS

SPE

SPE-214032-MS

Gas & Oil Technology Showcase and Conference

Country: Asia > Middle East > Iran > Arabian Gulf (0.54)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Asia > Middle East > Iran > Arabian Gulf > Arabian Basin > Arabian Gulf Basin > South Pars Field > Upper Khuff Formation (0.99)
Asia > Middle East > Iran > Arabian Gulf > Arabian Basin > Arabian Gulf Basin > South Pars Field > Upper Dalan Member (0.99)
Asia > Middle East > Iran > Arabian Gulf > Arabian Basin > Arabian Gulf Basin > South Pars Field > Sudair Formation (0.99)
(5 more...)

SPE Disciplines:

Well Drilling > Drilling Operations (1.00)
Management > Strategic Planning and Management > Project management (1.00)
Management > Professionalism, Training, and Education (1.00)
Data Science & Engineering Analytics > Information Management and Systems (1.00)

Technology: Information Technology (0.95)

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Developing a Spatial Framework for Ship Vulnerability Assessment Based on Category Theory

Ramezani, Abouzar (Sayyed Jamaleddin Asadabadi University, Asadabad) | Malek, Mohammad Reza (K.N. Toosi University of Technology, Tehran)

OnePetroMarch, 2023

Ships vulnerability analysis is one of the most important issues in today’s research, to reduce damage and increase safety. To increase the safety of ships, the effective parameters of the vulnerability of ships, the impact of each of them, and the relationship between these parameters should be identified to formulate different scenarios to analyze the vulnerability of ships. This process leads to the formation of simulation models to assess the risk of vessels. The creation of a spatial conceptual framework is needed to create integrated vulnerability models. The most important innovation of this research is the development of a spatial framework for analyzing ships’ vulnerability based on category theory. A framework that can be used to model the various scenarios of ships’ vulnerability from a variety of perspectives. To provide this framework, objects, operators, relationships, and assumptions for vulnerability analysis have been developed. To better express and convey the concepts, the spatial framework of the vulnerability analysis is presented in the form of category theory, which is a mathematical structure. The category theory is a good tool for expressing and creating a mathematical structure for objects and complex relationships in the real world, where other tools do not have this ability. The benefits of the built-in framework have been described with an integrated, precise mathematical structure that can be generalized to other subjects. Studies show that the developed framework is capable of modeling different scenarios for vulnerability analysis to find the best solution to reduce vulnerability.

OnePetro

doi: 10.5957/JOSR.02210003

SNAME

SNAME-JSR-02210003

Journal of Ship Research

Country:

Asia > Middle East > Iran (0.28)
North America > Canada (0.28)

Industry:

Government > Military > Navy (0.46)
Transportation > Marine (0.46)

SPE Disciplines:

Management > Risk Management and Decision-Making (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (0.46)
Health, Safety, Environment & Sustainability > Security > Facility vulnerability assessment (0.40)
(2 more...)

Technology: Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)

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Active Fault Detection by an Automatic Breakout Geometry Characterization Algorithm from Ultrasonic Borehole Imager

Heydari Gholanlo, Hamid (Faculty of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology) | Nikkhah, Majid (Faculty of Mining, Petroleum, and Geophysics Engineering, Shahrood University of Technology (Corresponding author))

OnePetroMarch, 2023

Summary An underground stress state might be disturbed in an area, particularly adjusting to an active shear zone. Borehole breakouts (BOs) that appeared in a circular hole excavated in an inhomogeneous stress field might be tracked to identify the active shear zone. The present study aims to develop the breakout morphology analysis (BMA) algorithm to exploit the valuable attributes of borehole BOs including azimuth, width, and intensity (depth of elongation) of failure from wellbore ultrasonic imaging tools. In the current study, the extracted azimuthal information was surveyed to detect the active shear zone along the well. Ultrasonic data from five wells drilled in the doubly plunging Ahvaz Anticline located in Iran were collected for the purpose of algorithm verification. The multiwell correlation of the BOs' azimuth generated by the algorithm in the Ahvaz Anticline suggests a shear plan dipping southwest-northeast direction is possibly active in the deep vertical wells. Similarly, the seismic reflection profile of the Ahvaz Anticline shows a track of detachment faulting system in the mid-Cretaceous sediments. The finding confirms that the raw ultrasonic traveling time is more applicable than other borehole image data, such as static and dynamic images of ultrasonic amplitude, in BO characterization. Introduction Perturbing the stress field by drilling a hole in the tectonically stable crust, compressive and tensile forces lead to derive some manifestations in the borehole's wall, namely BO and drilling-induced tensile fracture. BO is a key observation to assess the orientation and the magnitudes of the present-day stress state (Bell and Gough 1979; Simon 2012), which develops gradually with time in two sides of the borehole (Moore et al. 2011). The mechanism of BO propagation has been previously studied by researchers (Zoback 2007; Moore et al. 2011; Chandong and Casey 2012). Laboratory studies declared the alignment of BO's central axis is along with the remote field minimum horizontal stress (σ Every point in the upper lithosphere can be confined with forces, which might be different in magnitude. Beyond the vertical stress which stems from the overburden pressure, the evaluation of aerial tectonic can disturb the uniform horizontal forces inside the Earth. Also, the direction of principal horizontal stresses depends more on the regional convergence path.

OnePetro

doi: 10.2118/214673-PA

SPE

SPE-214673-PA

SPE Reservoir Evaluation & Engineering

Country: Asia > Middle East > Iran > Khuzestan > Ahvaz (0.76)

Genre: Research Report > New Finding (0.86)

Geologic Time: Phanerozoic > Mesozoic > Cretaceous (1.00)

Geophysics: Geophysics > Seismic Surveying > Borehole Seismic Surveying (1.00)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Treachery Formation (0.99)
Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Mt. Goodwin Formation (0.99)
Oceania > Australia > Western Australia > Timor Sea > Bonaparte Basin > WA-33-L > Block WA-279-P > Blacktip Field > Keyling Formation (0.99)
(11 more...)

SPE Disciplines:

Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (1.00)
Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Borehole imaging and wellbore seismic (1.00)

Technology:

Information Technology > Artificial Intelligence > Representation & Reasoning > Expert Systems (0.40)
Information Technology > Artificial Intelligence > Representation & Reasoning > Diagnosis (0.40)

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Automatic Interpretation of Oil and Gas Well Cement Evaluation Logs Using Fuzzy Convolutional Neural Networks

Saleh Nezhad, Mojtaba (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran) | Akbarizadeh, Gholamreza (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran (Corresponding author)) | Seifi Kavian, Yousef (Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran) | Salehi-Moorkani, Reza (National Iranian South Oil Company, Ahvaz, Iran)

OnePetroFebruary, 2023

Summary Cementing, as a common operation in well drilling and completions, requires accurate calculations and feasible studies. High-quality well cementing is necessary to achieve objectives and to prevent accidents and damage. The correct levels of cementation and cementation of good quality must be achieved, and thus both of these must be accurately evaluated. Cement bond quality can be assessed in various methods, for instance, the use of acoustic equipment. Acoustic readings can be processed to generate graphics of the cement status. These images are inspected by experts who assess the cement bonding visually, providing qualitative estimates of their quality. Regarding the explanations, industry needs automatic, fast, and intelligent methods. In this study, the performance of neural networks for automatic interpretation was evaluated and combined with fuzzy systems. We present a convolutional neural network (CNN) to address these challenges. The data were extracted from the oilwell logs of District 1 of Ahvaz, sampled by the National Iranian South Oil Company (NISOC), and were divided into three classes of cementing bond quality—namely, good, midrate, and bad. Each class contained 1 m data entries. The input to the CNN comprised images of sampled variable density logs (VDLs). In the second stage of analysis, the weights of the learned networks were optimized and replaced with a Bees algorithm (BA) and a fuzzy system (fuzzy-CNN). The estimated efficiency of the CNN to classify the well cement quality and fuzzy-CNN was 80.15 and 83.62%, respectively. The study provides insight into the efficiency and outputs of each of the networks studied. Problems encountered in training the networks to operate optimally as an automatic interpretation system were investigated and are discussed.

OnePetro

doi: 10.2118/214655-PA

SPE

SPE-214655-PA

SPE Drilling & Completion

Country: Asia > Middle East > Iran > Khuzestan > Ahvaz (0.25)

Genre: Research Report > New Finding (0.34)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places: Asia > Russia > Ural Federal District > Khanty-Mansi Autonomous Okrug > West Siberian Basin > Central Basin > Priobskoye (Northern Part) Field (0.99)

SPE Disciplines:

Well Drilling > Casing and Cementing > Cement and bond evaluation (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Neural networks (1.00)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)

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How Effective Is OPEC?

The Way AheadJanuary, 2023

The Organization of Petroleum Exporting Countries (OPEC) arose in response to the role of multinational oil companies as the price makers in the international crude market. In an effort to develop a stronger negotiating position, five countries--Iran, Iraq, Kuwait, Saudi Arabia, and Venezuela--founded OPEC in September 1960, with the mission "to coordinate and unify the petroleum policies of its Member Countries and ensure the stabilization of oil markets in order to secure an efficient, economic, and regular supply of petroleum to consumers, a steady income to producers, and a fair return on capital for those investing in the petroleum industry" (OPEC). Since its inception, the founding members have been joined by a rotating cast of other member countries. Currently, Algeria, Angola, Congo, Equatorial Guinea, Gabon, Libya, Nigeria, and the United Arab Emirates comprise the remaining eight of 13 members (Figure 1.) At the time of its inception, OPEC's five founding members controlled 80% of the world's crude exports (Yergin 2008).

The Way Ahead

Country:

Asia > Middle East > Saudi Arabia (0.31)
Asia > Middle East > Iraq (0.27)
Asia > Middle East > Iran (0.26)
(4 more...)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Government > Regional Government > North America Government > United States Government (0.74)

SPE Disciplines:

Management > Energy Economics (0.50)
Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (0.31)
Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (0.31)

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Tuned Low-Salinity Waterflooding in Carbonate Reservoirs: Impact of Cr2O72-, C6H5COO-, and SO42-

Ghalamizade Elyaderani, Seyed Masoud (Department of Petroleum Engineering, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran) | Saeedi Dehaghani, Amir Hossein (Department of Petroleum Engineering, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran (Corresponding author)) | Razavinezhad, Javad (Department of Petroleum Engineering, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran)

OnePetroJanuary, 2023

Summary Recent studies have revealed that tuning SO4 concentration can significantly boost low-salinity waterflooding (LSWF) in carbonate reservoirs. In this study, for the first time, Cr2O7 and C6H5COO were added to low-salinity water (LSW), and their effect on enhanced oil recovery (EOR) was investigated and compared with SO4. This study aimed to primarily determine whether adding anions other than SO4 to LSW could further reduce interfacial tension (IFT) and make the carbonate surface water-wet thereby improve oil recovery. To this end, we added Cr2O7, C6H5COO, and SO4 to LSW at different concentrations and performed IFT, contact angle, and zeta potential experiments. Then, the flooding test was carried out in a calcite-coated micromodel for each anion at the optimal concentration. The results showed that the carbonate surface became water-wet and intermediate-wet as the concentrations of Cr2O7 and SO4 increased, respectively. However, the presence of C6H5COO did not alter the carbonate surface wettability (i.e., it remained oil-wet). The calcite dissolution, ion pair formation, and salting-in effect mechanisms might alter the carbonate surface wettability. Also, IFT declined with increasing each anion concentration in LSW (with the highest reduction associated with Cr2O7), but this reduction was not significant. Several mechanisms might lead to the IFT reduction, including the salting-in effect, H effect, and surface excess concentration. Regarding zeta potential tests, although raising the concentrations of Cr2O7 and SO4 could make the charge of the carbonate surface more negative, increasing the concentration of C6H5COO had little effect on altering this charge. Additionally, Cr2O7 made the oil/brine zeta potential positive, although the oil/brine surface charge became negative in the presence of C6H5COO and SO4. As for anions’ affinity, Cr2O7 and C6H5COO had the highest and the lowest affinity for the interface, respectively. Besides, the amount of oil recovery for LSW was 18.7±1.6%. Compared with LSW, LSW2S and LSW1Cr raised oil recovery by 3.6 and 14.3%, respectively. The results of this study support that Cr2O7 can be used in LSWF. Indeed, this anion (compared with SO4) helps produce more oil from carbonate reservoirs by improving the parameters that are effective in EOR.

OnePetro

doi: 10.2118/214299-PA

SPE

SPE-214299-PA

SPE Journal

Country:

North America > United States (0.67)
Asia > Middle East > Iran (0.28)

Genre: Research Report > New Finding (1.00)

Industry:

Materials > Chemicals > Commodity Chemicals > Petrochemicals (1.00)
Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Asia > Middle East > Iran > Khuzestan > Arabian Basin > Widyan Basin > Mesopotamian Basin > West Karoun Block > West Karoun Field > Azadegan Field > Sarvak Formation (0.99)
Asia > Middle East > Iran > Khuzestan > Arabian Basin > Widyan Basin > Mesopotamian Basin > West Karoun Block > West Karoun Field > Azadegan Field > Kazhdumi Formation (0.99)
Asia > Middle East > Iran > Khuzestan > Arabian Basin > Widyan Basin > Mesopotamian Basin > West Karoun Block > West Karoun Field > Azadegan Field > Gadvan Formation (0.99)
Asia > Middle East > Iran > Khuzestan > Arabian Basin > Widyan Basin > Mesopotamian Basin > West Karoun Block > West Karoun Field > Azadegan Field > Fahliyan Formation (0.99)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Carbonate reservoirs (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)

Technology: Information Technology (0.47)

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Technology Focus: Mature Fields and Well Revitalization (January 2023)

Jain, Siddarth (Sharjah National Oil Corporation)

OnePetroJanuary, 2023

Capitalizing on untapped potential and quantifying risk is the key to success in a turbulent commodity industry. Mature fields have seen it all. Periods of high oil price have invited increased investment and pushed boundaries, while low-oil-price periods have had a severe effect on the fields’ sustainability and development. Mature fields have existed through a time of great technological change and stand on the cusp of their ultimate fate—either to maximize recovery with the lowest possible expenditures amid tightening environmental regulations or to close the taps and prepare for painful abandonments. In a capital-intensive industry, mistakes often are unforgiving and the costs of uncertainty and error are great. Fluctuating technological, political, and business influences add to the volatility and risk in selecting the next big idea for mature fields. The framework and success of future opportunities is reliant on the data used to quantify them, and this is something of which all mature fields have plenty. As they have delivered value throughout their life, the uncertainty associated with them reduces, and the new ideas discussed here come to light. Alternative use of wells for geothermal energy generation, carbon sequestration in depleted reservoirs, and the use of machine learning to maximize recovery are solutions that provide insight into how diverse the scope of mature field rejuvenation ideas can be. These solutions have something in common, however; they aim to capitalize on data, modularize problems, and structure a sustainable solution. These solutions are scalable, upgradable, and, most importantly, cost-effective for large and small operators. The upstream sector has long valued efficiency and accuracy. Small improvements in mature fields can make a significant economic difference with an established infrastructure in place. Value in large mature fields still exists, but one has to know where to look and what lenses to use. Recommended additional reading at OnePetro: www.onepetro.org. IPTC 21436 Permeability Prediction Using Rock Typing, Flow-Zone Indicator, and Machine-Learning Techniques in a Brownfield Offshore Malaysia by Budi Priyatna Kantaatmadja, Petronas, et al. SPE 208204 Generating Value From Mature Gas Fields by Quantifying Well-Integrity Assurance With a Critical Analysis of Multiple Logs and Retrieved Tubular Surface Inspection by Christna Golaco, Sharjah National Oil Corporation, et al. SPE 209988 Successful Reservoir Management and Optimization of Mature Steamflood Projects Using Artificial Intelligence by Andrei Popa, Chevron, et al.

OnePetro

doi: 10.2118/0123-0062-JPT

SPE

SPE-0123-0062-JPT

Journal of Petroleum Technology

Artificial Intelligence, asia government, enhanced recovery, iran government, JAIN, machine learning, mature fields, sharjah national oil corporation, SPE, Technology Focus, uae government, Upstream Oil & Gas, value, Well Revitalization

Country:

Asia > Middle East > Iran (0.42)
Asia > Middle East > UAE > Sharjah > Sharjah (0.31)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Improved and Enhanced Recovery (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology: Information Technology > Artificial Intelligence > Machine Learning (1.00)

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Collaborating Authors

Ultimate Shear Strength of Pitted Plates with Crack Using Finite Element Method

Estimation of Shear Wave Velocity Using Empirical, MLR, and GEP Techniques-Case Study: Kharg Island Offshore Oilfield

A New Approach of Petrophysical Rock Typing (PRT) for Carbonate Reservoir Using KNN Based on Conventional Wireline Data and Core Analysis Data

Essential Ingredients of Effective Project Management: A Case Study of Project Execution in the South Pars Mega-Projects

Developing a Spatial Framework for Ship Vulnerability Assessment Based on Category Theory

Active Fault Detection by an Automatic Breakout Geometry Characterization Algorithm from Ultrasonic Borehole Imager

Automatic Interpretation of Oil and Gas Well Cement Evaluation Logs Using Fuzzy Convolutional Neural Networks

How Effective Is OPEC?

Tuned Low-Salinity Waterflooding in Carbonate Reservoirs: Impact of Cr2O72-, C6H5COO-, and SO42-

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