bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Simulation Enhanced Oil Recovery Technique Screening in X and Y Fields Using a Combination of Analytical Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution
Authors: Priadi Sunni Nugraha , Ismoyo Hadi , Wahjudewanti Alexandra Sinta
Published: September 2021

The X and Y fields are among the oil fields in the Java basin, Indonesia. As oil production decreases due to exploitation activities in X and Y fields, it is necessary to carry out activities to increase production. To increase the yield of its oil production, Enhanced Oil Recovery (EOR) technology is needed. Enhanced oil recovery (EOR) technique screening analysis is needed to be carried out at the initial stage of the feasibility study in the EOR project. At present, there is no fully established method for identifying potential candidates for the EOR technique. The most common approach for selecting EOR techniques is conventional filtering, which is generally based on the "go-no go" trial and error, with a reduced chance of success. Besides, determining potential candidates for EOR techniques often uses a reservoirsimulation approach, but this is time-consuming and requires high costs in using the software license. EOR technique screening with a method that explains how to form a multi-criteria decision-making model with a combination of AHP and TOPSIS methods together as a systematic and measurable method to get the best EOR techniques in both X and Y fields.

The research results found that the CO2Immiscible Technique was the most appropriate for EOR in fields X and Y because it has the highest preference value (0.676), is then followed by the Micellar technique (preference value 0.645) and HC Immiscible (preference value 0.517). With the multi-criteria decision-making technique, the best EOR technique results are obtained.

Then the proposal can provide valuable recommendations for company management in both fields X and Y with a faster, accurate, and inexpensive method compared to the reservoir simulation method, which has a longer processing time and more expensive costs. This technique can support technology implementation decision-making in the early stages of EOR project development.
Business-Oriented Reserves and Resource Management - Experiences from a Merger
Authors: Dose Thies , Kachel Gunar
Published: September 2021

In May 2019, the merger between Wintershall GmbH and DEA Deutsche Erdoel AG was closed, which was the start of Wintershall Dea.This paper provides detailed insight into managing reserves and resource information during this merger.

After merger, three resource management activities required attention: (i) combining existing resources reporting, (ii) defining a lean but effective resources management and control system, and (iii) ensuring readiness for Initial Public Offering (IPO) by establishing an external independent evaluation of resources ("external resource audit"). This paper describes objectives, challenges and solutions on reserves and resources reporting of the new company.

The merged reserves and resources database of the previous year's reports had to consider audits from two different reporting systems in parallel to four different external auditors.With priorities defined by status of external auditing, operatorship and asset share a common database was derived and could immediately be used for financial transactions such as the issuance of an inaugural bond.

The new system for internal reporting of petroleum resources provides a fit-for-purpose approach, such as a consistent interpretation of commerciality criteria or definition of resources sub-classes.Particular attention was paid to synergies with respect to business planning, strategic portfolio analysis, and a link to technology & innovation. By defining specific attributes and sub-processes, the portfolio can be analyzed systematically. This provides additional insights and ensures synergies with business planning, strategic planning as well as internal technology initiatives.

A systematic resource control system is defined focusing on internal review, external and internal audits as well as synergetic use of project reviews. Moreover, a feedback loop for continuous improvement of reservoir management allows attending to important audit observations.

The external resource audit to ensure IPO readiness was structured to assign tasks for head office, business units and auditing company.The sequence of events from introduction to assets to reconciliation of differences between auditor and company was set-up, executed and monitored.Focus was on the definition of a structured but agile approach for external independent evaluation of all reserves and contingent resources.
Demystifying Openhole and Outer Casing Geometry and Annulus Material Characterization with Third Interface Echo TIE Response
Authors: Kumar Apoorva , Agrawal Gaurav , Singh Kamaljeet , Kumar Nitesh , Dutta Shaktim
Published: September 2021

Ultrasonic imaging based tools have been used for long for delivering high-resolution, comprehensive real-time confirmation of the pipe-to-cement bond quality and downhole pipe condition. However, for comprehensive analysis of cement barriers in challenging scenarios like lightweight cement and for better distinction between different annular materials downhole, a multi-physics evaluation has been developed which combines the measurements taken in thickness-mode with measurements taken in flexural-mode of the casing. Signals from these independent measurements are then processed to provide robust interpretation of solid-liquid-gas behind casing using acquired flexural attenuation and acoustic impedance data.

The information provided by the flexural attenuation is related to the state of the material in contact with the casing and does not probe deeper into the cement sheath. However, the pulse radiated by the flexural wave packet into the annulus may be reflected by the third interface, the interface with the formation or outer casing. The inner casing is fairly transparent to this reflected pulse so that it can also be picked by the receivers with significant amplitude. Since this reflected pulse propagate through the thickness of the annulus layer it may bring valuable information about the annulus geometry and material, and about the formation or outer casing geometry.

This paper demonstrates third interface echo principles and showcases several case studies for evaluating the outer casing geometry, annular material characterization, casing cut and pull depth suggestion and determining open hole size.
World First Commercial Application of Permanent Interventionless Monitoring Using Intelligent Inflow Gas Tracer Technology
Authors: Abdul Aziz Khairil Faiz , Mustafa Azreen , Wong Paul , Wurtz Marie , Leung Edmund , Overby Landrø Ståle , Koumouris Steve
Published: September 2021

Over the past decade, commercially available inflow tracers have been increasingly used to permanently monitor lower completions without the need for intervention. They have been designed to release selectively to oil or water, typically for clean-up verification, inflow quantification and identifying the location of water breakthrough in oil reservoirs.

Naturally, there has been an industry demand and requirement to develop inflow gas tracers to monitor gas reservoirs and identifying the location of gas breakthrough in oil reservoirs. In a green field development, it is important to obtain as much measurements as possible to understand completion efficiency and guide reservoir management decisions.

This paper presents the first commercial installation of inflow gas tracer technology that has been deployed in a dry gas field by HESS Malaysia in open hole stand-alone screen completions. It discusses the original monitoring objectives of this application in a full field development and how they evolved due to the gas tracer capabilities and the need for early well and field information. This paper will also discuss the retrofit screen design that allowed the gas tracers embedded in a polymer matrix called gas systems (GS) to be installed inside premium mesh screens.

At the wellsite, sampling campaign adjustments were executed depending on the flowing conditions during the clean-up, restarts to obtain relative flow contribution and inflow performance under multi-rate testing conditions.

Using a structured approach, the inflow gas monitoring project included feasibility studies, well candidate selection, lessons learnt and developed best practices based on installations in six producing wells in the North Malay Basin (NMB).
A Novel Approach to Determine Reservoir Fluid Composition from Separator Test Data
Authors: Sequeira Daryl S. , Egbukole Okechukwu M. , Sahl Ahmed M.
Published: September 2021

High quality composition and PVT data can directly improve a wide range of upstream and downstreamengineering calculations. The quality of PVT Black oil experiments depends on awide variety of factors that includes type of PVT system, pressure-temperature conditions, stability and composition. The objective of this study is to emphasize the need to use material balance calculations obtainedfrom separator test data to back-calculate the reservoir composition andvalidate it against the original reservoir fluid composition.

The methodologies employed in this study involve the following steps;
Change Management: A Game Changer for Effective Digital Transformation
Authors: Udofia Emmanuel , Stanley Buduka
Published: September 2021

Change Management is a process of adopting appropriate guidelines on how to manage change and meet the set business objective. Change Management could be extended into the realm of providing leadership for a group of persons or organisation alongside the path of change and embed the needed framework in actualising the set business target. Conversely, Digital Transformation could be described as the deployment of technology in a business process to amplify business benefits realisation that include fast decision-making, efficient business processes and significant reduction in risk exposure through managing the operational risk foot print. Failures of many Digital Transformation initiatives around the world is traceable to poor framing or complete lack of change management process embedment in the implemented digital solution, this paper aims at proposing effective framework for embedding orchestrated change process.

Several research works show that worldwide there are high rate of project failures in most digital oilfield implementations. The reasons for such high failure rate in the solution of Digital Transformation is poor or lack of experience in change management in such projects resulting in poor framing of the change process that will ultimately assist in orchestrating the disruptions that accompanies the implemented Digital Transformation in different assets. This research based project will be reviewing how effective change management process was implemented in a digital solution by an Oil and gas operator in a field offshore in sub-Saharan Africa. Elements such as proper engagement of the workforce, defined business processes, clear business objectives and experience of the change agents in managing previous projects will be evaluated because these are components that has been identified as key reasons for failure of the change management process implementation in most digital initiatives. What companies need to do is to be strategic with the approach of implementation of digital oilfields transformation to ensure that the disruption brought about by the digital oilfields solutions are orchestrated through effective change management embedment.

The effective change management process, when applied, shows that orchestrated technology disruption process is embedded which will ultimately not just lead to benefit realisation of the solutions but will assure continuous business improvement process, overtime. The result of this study, has shown that effective change management processes are beneficial to the effective embedment of Digital Oilfields Transformation solutions. Outcome of this study could form a reference tool for similar robust digital oilfields transformation, elsewhere.
Incorporation Project as a Tool for Students' Integration into the Company's Business Processes
Authors: Kartavy Sergei , Eremina Irina , Sorokin Pavel , Zalevina Anna , Pisarev Mikhail , Korkishko Alexander , Nabokov Alexander
Published: September 2021

The name Incorporation refers to the major purpose of project, which it to early integrate university students into the business processes of a vertically integrated oil company. Developed jointly with partner universities, the project was created as a response to several challenges of the company related to providing cross-functional cooperation and training of highly qualified personnel for the company as well as soft early adaptation into company.

Incorporation involves the integration of Industrial and Civil Engineering students into the phase of field concept design, and the further development of a strategy of a construction project based on the oil company's real case. So far, the Incorporation project has been applied in the perimeter of the Capital Construction and Conceptual Engineering functions of a major oil company, but as an educational tool it can be extended to other functions.

As a result of two full annual streams of the project, the students of Master's degree programmes Conceptual Engineering for the Oil and Gas Industry at University of Tyumen (UTMN) and Industrial and Civil Engineering of Oil Production Facilities at Industrial University of Tyumen (IUT) developed key skills and got a system view for the value chain. This promotes the career guidance of students and their subsequent employment in accordance with their expectations and skills.

This article highlights Incorporation background, its goal and objectives, principles and actors, includes a full description of one project stream as well as results over two years of Incorporation implementation in a large oil company.

The purpose of the article is to demonstrate existing best practices in the training of hard skills and team as well as personal soft skills among students of specific Master's degree programmes who makes a talent pool of oil company.
Automatable High Sensitivity Tracer Detection: Toward Tracer Data Enriched Production Management of Hydrocarbon Reservoirs
Authors: Ow Hooisweng , Chang Sehoon , Thomas Gawain , Wang Wei , Mashat Afnan A. , Shateeb Hussein
Published: September 2021

The development of automatable high sensitivity analytical methods for tracer detection has been one of the most central challenges to realize ubiquitous full-field tracer deployment to study reservoirs with many cross-communicating injector and producer wells. Herein we report a tracer analysis approach, inspired by strategies commonly utilized in the biotechnology industry, that directly addresses key limitations in process throughput, detection sensitivity and automation potential of state-of-the-art technologies.

A two-dimensional high performance liquid chromatography (2D-HPLC) method was developed for the rapid fluorescence detection and simultaneous identification of a class of novel barcoded tracers in produced water down to ultra-trace concentration ranges (<1ppb), matching the sensitivity of tracer technologies currently used in the oil industry. The sample preparation process throughput was significantly intensified by judicious adaptations of off-the-shelf biopharma automation solutions. The optical detection sensitivity was further improved by the time-resolved luminescence of the novel tracer materials that allows the negation of residual background signals from the produced water.

To showcase the potential, we applied this powerful separation and detection methodology to analyze field samples from two recent field validations of a novel class of optically detectable tracers, in which two novel tracers were injected along with a benchmarking conventional fluorobenzoic acid (FBA)-based tracer. The enhanced resolving power of the 2D chromatographic separation drastically suppressed the background signal, enabling the optical detection of a tracer species injected at 10x lower concentration. Further, we orthogonally confirmed the detection of this tracer species by the industry standard high-resolution accurate mass spectrometry (HRAM) technique, demonstrating comparable limits of detection. Tracer detection profile indicated that the transport behavior of the novel optical tracers through highly saline and retentive reservoir was similar to that of FBAs, validating the performance of this new class of tracers. Promising steps toward complete automation of the tracer separation and detection procedure have drastically reduced manual interventions and decreased the analysis cycle time, laying solid foundation to full-field deployment of tracers for better reservoir characterizations to inform decisions on production optimization.

This paper outlines the automatable tracer detection methodology that has been developed for robustness and simplicity, so that efficient utilization of the resultant high-resolution tracer data can be applied toward improving production strategy via intelligent and active rate adjustments.
Novel Application of Artificial Intelligence with Potential to Transform Well Planning Workflows on the Norwegian Continental Shelf
Authors: Vabø Jon Gustav , Delaney Evan Thomas , Savel Tom , Dolle Norbert
Published: September 2021

This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process.

Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard.

In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk.

Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft.

The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space).

The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives.

The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning.

Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows.

There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.
Natural Language Processing Applied to Reduction of False and Missed Alarms in Kick and Lost Circulation Detection
Authors: Yi Michael , Ashok Pradeepkumar , Ramos Dawson , Thetford Taylor , Bohlander Spencer , Moisan James , Behounek Michael
Published: September 2021

Kick and lost circulation events are large contributors to non-productive time. Therefore, early detection of these events is crucial. In the absence of good flow in and flow out sensors, pit volume trends offer the best possibility for influx/loss detection, but errors occur since external mud addition /removal to the pits is not monitored or sensed. The goal is to reduce false alarms caused by such mud additions and removal.

Data analyzed from over 100s of wells in North America show that mud addition and removal results in certain unique pit volume gain / loss trends, and these trends are quite different from a kick, a lost circulation or a wellbore breathing event trend. Additionally, driller's input text memos into the data aggregation system (EDR) and these memos often provide information with regards to pit operations. In this paper, we introduce a method that utilizes a Bayesian network to aggregate trends detected in time-series data with events identified by natural language processing (NLP) of driller memos critical to greatly improve the accuracy and robustness of kick and lost circulation detection.

The methodology was implemented in software that is currently running on rigs in North America. During the test phase, we applied it on several historical wells with lost circulation events and several historical wells with kick events. We were able to identify and quantify the losses even during connections and mud additions, where usually pit volume was increasing despite continual losses. Also, the real-time simultaneous analysis of driller memos provides context to pit volume trends and further reduce the false alarms. The algorithm is also able to take account of pit volume that was reduced due to drilling. Quantification of the losses offers more insight into what lost circulation material to use and the changes in the rate of loss while drilling. This approach was very robust in discovering kicks as well and differentiating it from mud addition and wellbore breathing events. These historical case studies will be detailed in this paper.

This is the first time that patterns in mud volume addition and removal detected from time-series data have been used along with driller memos using NLP to reduce false alerts in kick and lost circulation detection. This approach is particularly useful in identifying kick and lost circulation events from pit volume data, especially when good flow in and flow out sensors are not available. The paper provides guidance on how real-time sensor data can be combined with textual data to improve the outputs from an advisory system.
High-Purity, CO2-Free Hydrogen Generation from Crude Oils in Crushed Rocks Using Microwave Heating
Authors: Yuan Qingwang , Jie Xiangyu , Ren Bo
Published: September 2021

While the demand for hydrocarbon resources has been continuously increasing in the past 150 years, the industry is, however, criticized for carbon dioxide (CO2) emissions and concomitant global warming concerns. The oil and gas industry also face growing pressures in the ongoing energy transition. Generating and producing hydrogen (H2) directly from petroleum reservoirs has the potential to mitigate environmental impacts while revolutionizing the traditional petroleum industry and enabling it to become a clean hydrogen industry.

This paper proposes a novel approach to generate high-purity, CO2-free hydrogen from the abundant oil and gas resources in petroleum reservoirs using microwave heating. In this work, laboratory experiments were conducted to validate this scientific proof-of-concept and examine the roles of crushed rocks, catalysts, and water/oil ratio in hydrogen generation from crude oils in a reactor. A maximum of 63% ultimate hydrogen content is obtained in the generated gas mixtures, while the original CO2content in all experiments is negligible (<1%). Catalysts can promote hydrogen generation by accelerating rate and locally enhancing microwave (MW) absorption to create ‘super-hot spots'. Water also participates in reactions, and additional hydrogen is generated through water-gas shift reactions. The water-oil ratio in porous rocks affects the ultimate hydrogen yield. Overall, this research demonstrates the great potential of using MW heating to generate high-purity, CO2-free hydrogen from in situ petroleum reservoirs. Further research and wide application of this technology would potentially transform petroleum reservoirs to hydrogen generators, thus mitigating the environmental impacts of traditional petroleum industry while meeting the increasing demand for clean hydrogen energy. This technology would also benefit the safe transition towards a decarbonized society.
Design, Development and Installation of Modular Inflow Control Technology
Authors: Erives Valeria , Plooy Mike , Agnihotri Vivek , Dikshit Ashutosh , Kumar Amrendra , Gurbanov Seymur , Tripathi Abhinandan
Published: September 2021

Integrating a flow control sliding sleeve into a sand screen can provide multiple advantages to the user in controlling the production inflow. Although it does come with an increased completion cost as well as the number of interventions required when its time to operate those valves. Especially in long horizontal wells, this can become time consuming and inefficient. A few technologies exist to address this issue but they are either too complex or require specialized rigging equipment at the wellsite, which is not desirable. As described herein, a unique, fit for application modular sliding sleeve sand screen assembly with dissolvable plugs was developed that eliminates wash-pipe and allows flow from several screens controlled via a single sliding sleeve. Design and field installation of these modular screens is presented in this paper. The new modular sand-screen consisted of an upper joint, modular middle joint, modular middle joint with ICD/SSD (w/ optional dissolvable plugs), and a lower joint, and novel field installable flow couplings between them. The design allowed for any number of non-ICD/SSD screen joints to be connected to any number of ICD/SSD joints in any order. A computer-aided design was followed to achieve all the operational/mechanical requirements, Computational fluid dynamics (CFD) was used to optimize the flow performance characteristics. Prototypes were manufactured and tested prior to conducting successful field trials.

The conceptualization and design stage provided several challenges as different ways to achieving modularity and interconnectivity were explored (such as internal to the tubing or external, sealing methods, ease of installation, reliability). Several design calculations were performed to select the most robust design and most suitable solution for the application. Design for manufacturing review, design calculations and CFD analysis helped with the selection of a concept that maximized the flow rates and kept flow velocity under the limit through the critical sections. Dissolvable plugs were used to temporarily close the SSD ports for wash-pipe free installation. The sealing mechanism of plugs was confirmed by differential pressure test up to 500 psi. A valuable, new downhole modular screen design for use w/ICD/SSD providing intervention-less completions without involving complex/expensive technologies is developed, tested and installed. A new, field-proven, modular sand control technology allowing flow from several non-ICD/SSD screen joints to drain into a single ICD/SSD joint, thus eliminating the need to run ICD/SSD on every screen joint in an unconsolidated formation is developed. Dissolvable plug integrated into sliding sleeve ports allowed wash pipe free installation. The technology allows increasing/decreasing the total drainage length at the well site per zonal requirements, thereby reducing costs and improving performance.
A Hybrid Petroleum Fiscal System for Investment in the Exploration and Production E&P of Hydrocarbon
Authors: Ogolo Oghenerume , Nzerem Petrus , Okafor Ikechukwu , Abubakar Raji , Mahmoud Mohamed , Kalu George
Published: September 2021

Globally, there are two types of petroleum fiscal system; the concessionary and the contractual petroleum fiscal system. The main differences between the two types of petroleum fiscal system is the ownership of the resources and some distinct fiscal terms. The contractual petroleum fiscal system specifies a cost recovery option and profit oil split unlike the concessionary petroleum fiscal system that allows the contractor to recoup his capital before payment of tax. This tends to increase the risk associated with the host government revenue as investment in the production of hydrocarbon is filled with uncertainties. There is a need to redesign the concessionary petroleum fiscal to enable it reduce the risk associated with the host government revenue by making the host government to earn revenue early from petroleum investment. This research therefore evaluated a hybrid petroleum fiscal system for investment in the exploration and production of hydrocarbon. The concessionary petroleum fiscal system was adjusted to include a cost recovery option. Petroleum economic model for investment in a typical onshore oil field was built using spreadsheet modelling technique with the fiscal terms in the hybrid petroleum fiscal system embedded in it. The cost recovery option and oil price in the model were varied between 0-100% and $20-$100 per barrel. The NCF, IRR and payout period of the investment were determined. It was observed that the lower the cost recovery option, the higher the host government revenue. From the profitability analysis of the investment in the hybrid petroleum fiscal system, it was observed that when the price of oil was $100/bbl, the NCF of the host government was $9146 and $8426.3 for 0% and 80% cost recovery option. The lower the cost recovery option, the higher the payout period and the lower the internal rate of return. Though lower cost recovery increased the host government revenue more but it may make the hybrid petroleum fiscal system unattractive for investment in periods of low oil price. Hence a higher cost recovery option was recommended for the use of this type of petroleum fiscal system.
Bit Design Methodology to Mitigate High-Frequency Torsional Oscillation
Authors: Tipples Rob , Keshiyev Sahet , Sheikhrezaei Kian , Centala Prabhakaran
Published: September 2021

This paper reviews field data where high-frequency torsional oscillation (HFTO) was seen on previous bit runs and hypothesizes on features or design metrics that may have directly influenced this vibration. This paper investigates four metrics of bit design: Cutter wear, shear length:shear area ratio, choice of secondary cutter material, and effective backrake. Hypotheses are established linking these metrics to HFTO, and then data from field runs is shown to correlate the hypotheses. At this point, a bit was designed and manufactured to put the HFTO avoidance hypotheses into practice. Prior to laboratory testing, a theoretical model is used to identify resonant torsional frequencies. A series of laboratory experiments followed to test the hypotheses and demonstrated that there is correlation between all factors, but in one case is counter to the hypothesis.

This information is of use when selecting or designing bits in environments where HFTO is known to occur. The findings may also assist in explaining performance that's below expectations where HFTO is not able to be explicitly measured.
Well Interference Detection from Long-Term Pressure Data Using Machine Learning and Multiresolution Analysis
Authors: Orta Aleman Dante , Horne Roland
Published: September 2021

Knowledge of reservoir heterogeneity and connectivity is fundamental for reservoir management. Methods such as interference tests or tracers have been developed to obtain that knowledge from dynamic data. However, detecting well connectivity using interference tests requires long periods of time with a stable reservoir pressure and constant flow-rate conditions. Conversely, the long duration and high frequency of well production data have high value for detecting connectivity if noise, abrupt changes in flow-rate and missing data are dealt with. In this work, a methodology to detect interference from longterm pressure and flow-rate data was developed using multiresolution analysis in combination with machine learning algorithms. The methodology presents high accuracy and robustness to noise while requiring little to no data preprocessing.

The methodology builds on previous work using the Maximal Overlap Wavelet Transform (MODWT) to analyze long-term pressure data. The new approach uses the ability of the MODWT to capture, synthesize and discriminate the relevant reservoir response for each individual well at different time scales while still honoring the relevant flow-physics. By first applying the MODWT to the flow rate history, a machine learning algorithm was used to estimate the pressure response of each well as it would be in isolation. Interference can be detected by comparing the output of the machine learning model with the unprocessed pressure data.

A set of machine learning, and deep learning algorithms were tested including Kernel Ridge Regression, Lasso Regression and Recurrent Neural Networks. The machine learning models were able to detect interference at different distances even with the presence of high noise and missing data. The results were validated by comparing the machine learning output with the theoretical pressure response of wells in isolation. Additionally, it was proved that applying the MODWT multiresolution analysis to pressure and flow-rate data creates a set of "virtual wells" that still follow the diffusion equation and allow for a simplified analysis.

By using production data, the proposed methodology allows for the detection of interference effects without the need of a stabilized pressure field. This allows for a significant cost reduction and no operational overhead because the detection does not require well shut-ins and it can be done regardless of operation opportunities or project objectives. Additionally, the long-term nature of production data can detect connectivity even at long distances even in the presence of noise and incomplete data.
Evaluation of Machine Learning Methodologies Using Simple Physics Based Conceptual Models for Flow in Porous Media
Authors: Magzymov Daulet , Ratnakar Ram R. , Dindoruk Birol , Johns Russell T.
Published: September 2021

Machine learning (ML) techniques have drawn much attention in the engineering community due to recent advances in computational techniques and an enabling environment. However, often they are treated as black-box tools, which should be examined for their robustness and range of validity/applicability. This research presents an evaluation of their application to flow/transport in porous media, where exact solutions (obtained from physics-based models) are used to train ML algorithms to establish when and how these ML algorithms fail to predict the first order flow-physics. Exact solutions are used so as not to introduce artifacts from the numerical solutions.

To test, validate, and predict the physics of flow in porous media using ML algorithms, one needs a reliable set of data that may not be readily available and/or the data might not be in suitable form (i.e. incomplete/missing reporting, metadata, or other relevant peripheral information). To overcome this, we first generate structured datasets for flow in porous media using simple representative building blocks of flow physics such as Buckley-Leverett, convection-dispersion equations, and viscous fingering. Then, the outcomes from those equations are fed into ML algorithms to examine their robustness and predictive strength of the key features, such as breakthrough time, and saturation and component profiles. In this research, we show that a physics-informed ML algorithm can capture the physical behavior and effects of various physical parameters (even when shocks and sharp gradients are present). Further the ML approach can be utilized to solve inverse problems to estimate physical parameters.
Low Adsorbing CO2 Soluble Surfactants for Commercially Viable Implementation of CO2 Foam EOR Technology
Authors: Katiyar Amit , Knight Troy , Grzesiak Adam , Rozowski Pete , Nguyen Quoc
Published: September 2021

Several gas Enhanced Oil Recovery (EOR) pilots enhanced with aqueous-foam based conformance solutions have been implemented in the last 30 years. While these pilots were technically successful, there were economic challenges limiting their commercial viability. Many of these pilots were implemented with water-soluble foaming surfactants that can get adversely affected by near wellbore gas-water gravity segregation and adsorption loss up to 90% of the injected surfactant. Novel, gas-soluble surfactants can be injected with the gas phase where these surfactants are carried with the gas to thief zones faster and deeper with relatively lower adsorption to the rock surface. However, the conventional foam modeling approach relied only on the surfactant concentration in brine to determine foam strength, which adversely predicted the performance of gas soluble surfactants. With proven laboratory evaluations and multiple successful field implementations, the advantages of low adsorbing and gas soluble surfactants cannot be ignored. In this paper, the advantages of surfactant partitioning to the gas phase are confirmed by correcting the conventional foam modeling approach while simulating 1D transport of CO2-foam displacing brine in porous media.

An empirical foam model was developed from the lab scale core flooding work of CO2foam transport through porous media using a novel gas-soluble foaming surfactant. While investigating the performance of gas soluble surfactants, global surfactant concentration was used to determine foam strength as the surfactant can transport to the gas-water interface from both the phases. Lab experiments and simulations with an improved foam modeling approach confirmed that a higher gas phase partitioning surfactant generated robust foam and deeper foam propagation while injecting surfactant with CO2in a water saturated core. In addition, comparing three partition coefficient scenarios around 1 on mass basis, the higher gas phase partitioning surfactant showed the larger delay in gas breakthrough. Overall, the simulation results with our better modeling approach do support the advantages of the higher gas phase surfactant partitioning in deeper foam transport and conformance enhancement for the gas-EOR technology.
An Integrated Workflow for Reserves Evaluation in the U.S. Permian Basin Based on SPEE Monograph 3
Authors: Xia Xiaoyang , Nelson Eric , Olds Dan , Connor Larry , Zhang He
Published: September 2021

In 2011, the Society of Petroleum Evaluation Engineers (SPEE) published Monograph 3 as an industry guideline for reserves evaluation of unconventionals, especially for probabilistic approaches. This paper illustrates the workflow recommended by Monograph 3. The authors also point out some dilemmas one may encounter when applying the guidelines. Finally, the authors suggest remedies to mitigate limitations and improve the utility of the approach.

This case study includes about 300 producing shale wells in the Permian Basin. Referring to Monograph 3, analogous wells were identified based on location, geology, drilling-and-completion (D&C) technology; Technically Recoverable Resources (TRRs) of these analogous wells were then evaluated by Decline Curve Analysis (DCA). Next, five type-wells were developed with different statistical characteristics. Lastly, a number of drilling opportunities were identified and, consequently, a Monte Carlo simulation was conducted to develop a statistical distribution for undeveloped locations in each type-well area.

The authors demonstrated the use of probit plots and demonstrated the binning strategy, which could best represent the study area. The authors tuned the binning strategy based on multiple yardsticks, including median values of normalized TRRs per lateral length, slopes of the distribution lines in lognormal plots, ratios of P10 over P90, and well counts in each type-well category in addition to other variables. The binning trials were based on different geographic areas, producing reservoirs, and operators, and included the relatively new concept of a "learning curve" introduced by the Society of Petroleum Engineers (SPE) 2018 Petroleum Resources Management System (PRMS). To the best of the authors’ knowledge, this paper represents the first published case study to factor in the "learning curves" method. This paper automated the illustrated workflow through coded database queries or manipulation, which resulted in high efficiencies for multiple trials on binning strategy. The demonstrated case study illustrates valid decision-making processes based on data analytics. The case study further identifies methods to eliminate bias, and present independent objective reserves evaluations. Most of the challenges and situations herein are not fully addressed in Monograph 3 and are not documented in the regulations of the U.S. Security and Exchange Commission (SEC) or in the PRMS guidelines. While there may be differing approaches, and some analysts may prefer alternate methods, the authors believe that the items presented herein will benefit many who are starting to incorporate Monograph 3 in their work process. The authors hope that this paper will encourage additional discussion in our industry.
New and Improved Single-Aqueous-Phase Retarded Acid SAPRA - Performance, Pore Volume Break through, and Wormhole Characterization
Authors: Wu Jing , Monette Matthew , Sickorez Jeff , Street Joseph , Tonmukayakul Peng , Lee Jesse , Craig Steven , Nguyen Quoc , Craig Steven
Published: September 2021

Controlling the reactivity of HCl is the most viable approach to successfully stimulate a high-temperature carbonate reservoir. It is essential to retard the HCl-carbonate rock reaction to achieve the optimum balance between total fluid used and enhancing well production. However, drawbacks intrinsic to the technology architectures have prevented the industry-wide adoption of these inventions. For instance, the conventional emulsified acid is well documented to exhibit high friction pressure, is cumbersome to prepare, and performance is sensitive to a multitude of parameters. The recently developed singleaqueous-phase retarded acid (SAPRA) represents one big step toward the right direction, but there is certainly ample room for improvement. This paper presents the next generation of SAPRA system and its laboratory findings. In this system, the HCl reactivity is regulated and retarded by a single, potent low-dosage additive, which is compatible with selected acid corrosion inhibitors, non-emulsifiers, H2S scavengers, and other commonly used additives, and if necessary, friction reducers as well.
Parameter Evaluations for Vertical Wells with Hydraulic Fracture Using Well-Testing and Deep Learning Method
Authors: Chen Zhiming , Dong Peng , Meng Meiling , Wang Jianan , Wang Tianyi , Li Dexuan
Published: September 2021

The reliability of well-testing interpretation largely depends on the experience of reservoir engineers, which make the issue of non-unique solution serious and increase its application threshold. Virtually, deep learning assistive techniques are good strategies in well-testing interpretation. Although some work has been done based on automatic interpretation techniques, there is still a lack of an automatic interpretation model with wide applicability and fast interpretation on parameter evaluation of vertically fractured well.

To improve this situation and make the well-testing interpretation easier to apply, this paper uses deep learning methods to build an automatic interpretation model of well-testing data for vertically fractured well. The model can automatically identify the corresponding parameters. The results in the validation set show that the median relative error of the curve parameter inversion is less than 10%. In addition, the accuracy of parameter prediction can be improved by increasing the weight of some important parameters in deep learning model training, such as permeability and fracture half-length. Finally, the automatic interpretation model is tested on a field case. The test results prove that the model has high accuracy and interpretation speed.
Novel Completion Designs in Horizontal Well with Transverse Hydraulic Fractures for Enhanced Recovery in Unconventional or Tight Reservoirs
Authors: Mishra Shubham , Fredd Christopher , Wilberg Dean , Yanbollu Umur
Published: September 2021

Low recovery, 2 to 15%, in unconventional plays (including tight reservoirs and source rocks) has long been recognized as a business deterrent. The industry applies enhanced oil recovery (EOR) techniques, along with hydraulic fractures in tight/unconventional plays, to improve the recovery. To maximize matrix sweep, the fractures are aligned in a face-to-face assembly. Such an arrangement can be achieved using vertical or longitudinal hydraulic fracture on horizontal wells, but these, generally, do not provide as effective reservoir contact (hydraulic fracture surface area) as horizontal wells with multistage transverse hydraulic fractures. The multistage transverse hydraulic fracture, however, comes at the costs of conformance issues with early water breakthrough from short-circuiting and inability to achieve fracture face-to-fracture face alignment of the injection and production fractures. The vast majority of wells drilled in unconventional plays are in the transverse configuration; hence, there is a need for an optimal solution for transverse fractures combined with improved oil recovery (IOR)/EOR approaches.

In this work, we introduce the multistage enhanced recovery (MS-ER) techniques that enable face-to-face alignment for optimal enhanced hydrocarbon recovery/IOR/EOR in horizontal wells with multistage transverse fractures, thereby enabling optimal recovery and mitigating the key risk of fracture short-circuiting.
Enhancement of Indistinct Sequence Stratigraphic Correlations Using Geochemical Signatures: An Example from the Paleozoic Successions Saudi Arabia
Authors: Hussain Maaruf , Amao Abduljamiu , Al-Ramadan Khalid , Babalola Lamidi , Humphrey John
Published: September 2021

The Paleozoic sequence in Kingdom of Saudi Arabia (KSA) represents a thick succession of carbonate, shale, and siltstone/sandstone lithologies that were deposited in a range of environments. This succession hosts abundant unconventional reservoirs with huge amount of natural gas reserves. However, similarity in lithologies and poor biostratigraphic constrains are making facies analysis, stratigraphic correlation, and geosteering applications problematic. In this study, we documented the use of an automated statistical protocol for the identification of chemofacies and correlatable chemozones within highly homogenous formations.