|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
Green fields today mostly can be regarded as marginal fields and successfully developed. It covers the complete assessment of the oil and gas recovery potential from reservoir structure and formation evaluation, oil and gas reserve mapping, their uncertainties and risks management, feasible reservoir fluid depletion approaches, and to the construction of integrated production systems for cost effective development of the green fields. Depth conversion of time interpretations is a basic skill set for interpreters. There is no single methodology that is optimal for all cases. Next, appropriate depth methods will be presented. Depth imaging should be considered an integral component of interpretation. If the results derived from depth imaging are intended to mitigate risk, the interpreter must actively guide the process.
Decisions in E&P ventures are affected by Bias, Blindness, and Illusions (BBI) which permeate our analyses, interpretations and decisions. This one-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact. Bias refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion. Blindness is the condition where we fail to see an unexpected event in plain sight. Illusions refer to misleading beliefs based on a false impression of reality. All three can lead to poor decisions regarding which work to undertake, what issues to focus on, and whether to forge ahead or walk away from a project. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders. Examples are provided including corporate, business unit and department case studies. This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders. Examples are provided including corporate, business unit and department case studies. Safety leadership focuses on the Human Factors (HF) which complement technical training to optimise reliability, safety, compliance, efficiency, and risks within a team-based environment. The IOGP laid down the HF skills and competencies required, and they form the basis for specialised O&G HF training's delivered by Mission Performance. This 1-day course reviews the key human factors but then also reviews what can be done to accelerate and scale operational roll-out for optimum and sustained impact, including integration with existing safety processes and (reporting) systems, refreshers, assessments, measurements, as well as the role of leadership and culture. Decisions in E&P ventures are affected by Bias, Blindness, and Illusions (BBI) which permeate our analyses, interpretations and decisions. This one-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact. Bias refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion.
Take Back Control of Your Capital Project with an EPC 4.0 Strategy Stratigraphical - Sedimentological Framework For The Thamama Group Development In The Western Uae Based On The Legacy Core Data: How The Key To The Future Is Found In The Past. Performance Comparison Of Two Different In-house Built Virtual Metering Systems For Production Back Allocation. Innovation In A Time Of Crisis: How Can The Upstream Industry Develop New, Fit-for-purpose Technology? How To Meet Operational Challenges In An Extreme VUCA Environment By Adaptive Process Control. Challenges In Drilling & Completion Of Extended Reach Drilling Wells With Landing Point Departure More Than 10,000ft In Light/ Slim Casing Design.
Ramdani, Ahmad (King Abdullah University of Science and Technology) | Chandra, Viswasanthi (King Abdullah University of Science and Technology) | Finkbbeiner, Thomas (King Abdullah University of Science and Technology) | Khanna, Pankaj (King Abdullah University of Science and Technology) | Vahrenkamp, Volker (King Abdullah University of Science and Technology)
Microporosity is volumetrically the most important porosity type in the giant carbonate reservoirs of Arabia and can significantly impact reservoir quality and ultimate oil recovery. Understanding the impact of microporosity on reservoir quality and accurately predicting the spatial distribution of microporosity at the reservoir scale is required to improve the recovery of remaining hydrocarbons from the reservoirs. Utilizing an integrated data analysis approach applied to multi-scale geological and geophysical datasets from micrometer scale SEM imagery to decameter scale seismic data, we predict the distribution of microporosity at the reservoir grid-block scale. We apply the proposed methodology to Arab-D reservoir equivalent outcrop data from the Upper Jubaila Formation, Saudi Arabia. Thirty-five meters of near-surface well core and a 600 m long 2D near-surface p-wave seismic reflection profile were acquired at the outcrop location. From the core, 106 plug samples are analysed to determine porosity and permeability, ultrasonic velocities, powder XRD compositions, and SEM data. With the seismic reflection data, we perform a near-surface colored inversion to obtain a high-resolution acoustic impedance image of the seismic data. The morphology of micrite crystals that host microporosity was characterized and quantified by analysing SEM data using machine learning image classification tools. We use the resulting data to derive robust statistical relationships between microporosity and texture of micrite microcrystals on centimetre scale geophysical properties with a Self-Organizing Map (SOM) approach for data clustering. A Differential Effective Medium (DEM) model enabled us to correlate acoustic impedance and porosity, and distribute porosity across the 2D seismic cross-section. The key depositional lithofacies identified from core descriptions are bioturbated mudstones intercalated by packstones and grain dominated rudstones and floatstones. Image-based machine learning classification results indicate that microcrystals that host microporosity in this formation were typically homogenous in size but varied in morphological aspects such as granularity and angularity. Based on data clustering results, granularity and angularity of microcrystals appear to be the dominant controls over the lab-measured geophysical properties. This effect is manifested as a simple log-linear relationship between porosity and permeability among the major depositional facies. The DEM fitting parameter effectively represents the velocity-porosity relationship and can be used to predict the distribution of porosity across a seismic cross-section. For the first time, an integrated multi-scale data methodology involving machine leaning tools is applied to the Late Jurassic Upper Jubaila Formation outcrop data. Although we demonstrate the proposed methodology using outcrop data, it can be applied to any subsurface reservoir zone dominated by microporosity.
Maalouf, Janine (Schlumberger) | Benny, Praveen Joseph (Schlumberger) | Cantarelli, Elena (Schlumberger) | Al-Hassani, Sultan Dahi (ADNOC Offshore) | Altameemi, Ibrahim Mohamed (ADNOC Offshore) | Ahmed, Shafiq Naseem (ADNOC Offshore) | Khan, Owais Ameer (ADNOC Offshore) | Al Hammadi, Mariam Khaleel (ADNOC Offshore) | Zakaria, Hasan Mohammed (ADNOC Offshore) | Aboujmeih, Hassan Fathi (ADNOC Offshore)
Ultrahigh-resolution electrical images (UHRIs) acquired with logging while drilling (LWD) tools have brought to light different side effects of using drilling tools such as rotary steerable systems (RSSs) and bits when drilling a horizontal borehole. This paper will go through the extensive analysis and simulations that followed, gathering data from almost thirty wells, to try and understand the root causes behind these side effects, along with the actions put in place to mitigate it. UHRIs were used while drilling a 6-in horizontal hole to achieve a 100% net-to-gross and perform advanced formation evaluation to optimize well production. Surprisingly, these images revealed more details: wellbore threading–a type of spiral–inside the formation. To understand the cause behind such marks, RSS and bit data was gathered from around thirty wells, compared, and analyzed. Simulations were run over months, considering rock types, drilling parameters, and bottom hole assembly (BHA) design to reproduce the issue and propose the best solution to prevent these events from reoccurring. After the data compilation, a trend emerged. Wellbore threading was observed in soft, high-porosity reservoir formations. It also appeared in tandem with controlled rate of penetration (ROP), low weight on bit (WOB), and a low steering ratio. At this point, advanced analysis and simulations were needed to determine the root cause of this phenomenon. A Finite Element Analysis (FEA) based 4D modeling software showed that the bit gauge pad length, combined with the RSS pad force, contributed to this threading. A pad pressure force higher than 7,000 N in conjunction with a short-gauge bit increased the likelihood of having this borehole deformation. Simulations comparing different size tapered and nominal bit gauge pad lengths were run to determine the effect on the borehole and on the steerability. Bit design is directly linked to the wellbore threading effect. It is more pronounced when associated with a powerful rotary steerable system and in a soft formation environment. However, altering a specific bit design can have a direct and undesirable effect on the steerability of the BHA. UHRI revealed details of borehole deformation that new drilling technologies are causing. It enabled an in-depth analysis of the different causes behind it, revealing ad-hoc solutions.
Horizontal wells are being drilled in more challenging environments such as through thin formation layers, unpredictable geology, and unknown fluid movement. Detailed evaluation has a direct impact on the completion approach. But we also need to drill faster and more efficiently. The wellbore threading caused formation damage that masked information needed for formation evaluation. In a novel application of UHRI data, simulations gave birth to information which has been lacking and incentivized the development of new, formation-friendly technology.
Bin Ishaq, Wala (ADNOC Sour Gas) | Al Darmaki, Fatima (ADNOC Sour Gas) | Lucas, Noel (ADNOC Sour Gas) | Al Mansoori, Mohamed (ADNOC Sour Gas) | Deville De Periere, Matthieu (Badley Ashton and Associates Ltd) | Foote, Alexander (Badley Ashton and Associates Ltd) | Bertouche, Meriem (Badley Ashton and Associates Ltd) | Durlet, Christophe (Laboratoire Biogeosciences)
In the onshore sector of the United Arab Emirates, the Lower Arab D Member (Kimmeridgian) typically encompasses a thick succession of rather homogeneous low-energy mid-ramp carbonate mudstones interbedded with minor storm-induced cm-scale skeletal-rich floatstones. Within these deposits, the pore volume is dominated by locally abundant matrix-hosted micropores, along with variably abundant open to partially cemented fractures, primary intraparticle macropores and rare moulds and vugs. As a result of this variably developed pore system, measured porosity varies from poor to very good, while permeability changes from extremely poor to rarely good. Detailed petrographic observations (thin-sections, SEM) carried out within six cored wells in a sour gas reservoir highlight that the variations in reservoir properties are primarily linked to the micron-scale variations in the micritic fabric. Indeed, anhedral compact micrites with coalescent intercrystalline contacts are associated with very small and poorly connected micropores, while polyhedral to subrounded micrites with facial to subpunctic intercrystalline contacts show locally well-developed micropores and therefore better reservoir potential. δ18O and δ13C isotope measurements do not discriminate both micritic fabrics, indicating a recrystallisation of the matrix within shallow burial conditions. However, bulk XRF measurements, and especially SiO2, Al2O3 and Fe2O3 content indicate that poorly porous anhedral compact micrite host more insoluble material and have been prone to a greater compaction compared to porous polyhedral micrites. Log-derived elastic properties, including Young's Modulus (YME) along with porosity data, have been used in two wells to explore the potential relationship between micritic fabric, porosity, permeability and elastic properties. With the evolution of micritic fabric from anhedral compact to polyhedral / subrounded, Young's Modulus decreases with increasing porosity, indicating a decrease in the overall stiffness of the rock. Based on these two learning wells, specific porosity and YME cut-offs have been identified to discriminate the various micrite fabrics. Those cut-offs have been successfully tested in four other wells used as a blind test for the vertical prediction of the micritic fabrics, in which accurate predictions reached up to 90%. Following these results, porosity and YME cut-offs have been used to produce the first model of the distribution of the various micritic fabrics at the field-scale. These results have a fundamental impact on how sedimentologically homogenous microporous limestones can be described and predicted at the well and field-scales, especially in the context of exploring tight carbonate plays associated with intrashelf basins.
Al-Hassani, Sultan Dahi (ADNOC Offshore) | Altameemi, Ibrahim Mohamed (ADNOC Offshore) | Ahmed, Shafiq Naseem (ADNOC Offshore) | Khan, Owais Ameer (ADNOC Offshore) | Al Hammadi, Mariam Khaleel (ADNOC Offshore) | Zakaria, Hasan Mohammed (ADNOC Offshore) | Saqib, Talha (ADNOC Offshore) | Fernandes, Warren (BHGE) | Potshangbam, Sanathoi (BHGE) | Saravanakumar, Krishnan (BHGE) | Hassan, Syed (BHGE)
Undeveloped reservoirs poses many uncertainties in terms of reservoir structural control and inherent properties and as a result integrated fit for purpose engineering and technology plays a vital role to drill, appraise and complete a well successfully. While Maximum Reservoir Contact (MRC) wells show promise in increased deliverability, sustainability and cumulative recovery, the risk of high cost, reduced well life and sustainability issues can become real if the well is not planned, executed and appraised properly.
This paper focuses on the integrated multi-disciplinary approach between Reservoir Engineering, Petroleum Engineering, Drilling and Geoscience functions to achieve MRC of 8,500 ft. in two sublayers of 3 ft. each while mapping and avoiding any potential risk for water zones. Data acquisition pertaining to reservoir characterization, fracture and fault identification was planned to enhance this undeveloped reservoir understanding and to optimize lower completion design.
3D real-time multiwell reservoir modelling and updating capabilities with appropriate LWD measurements for Proactive Geosteering and Formation Evaluation was planned. Based on forward response model from offset well data along with drilling engineering and data acquisition requirements, an LWD suite consisting of RSS, Gamma Ray Image, High Resolution Resistivity Image (Fracture and Fault identification), NMR (both Total and Partial Porosities, and T2 Distribution) along with a Deep Azimuthal Resistivity measurement for early detection and avoidance of conductive/water zones was utilized.
Achieved a field record of the longest drain drilled with 8,500 ft. of MRC. The fit for purpose real time LWD measurements enabled successful placement of the lower completion and blanking the risk zones for pro-longed sustainable production. Identification of fracture zones in real time helped in optimizing the completion plan while drilling. Based on this well's results, it is established that replicating the same practice could positively affect the overall Field Development potential. The same technique is planned for the future development of undeveloped reservoirs in this field.
Yugay, Andrey (ADNOC Onshore) | Ahmad, Mubashir (ADNOC Onshore) | Bankole, Ibukun Olatunbosun (ADNOC Onshore) | Alhouqani, Shamsa Sulaiman (ADNOC Onshore) | Al Qallabi, Salah Al Deen (ADNOC Onshore) | Pimenta, Gervasio (ADNOC Onshore)
As a part of Country strategy to fulfill growing demand in gas energy in the country, development of Arab formations started. This paper shares the actual case history of successfully completed evaluation of Arab formation in one of the Company fields. High temperature (300F), high H2S concentrations (up to 37% H2S) and presence of elemental Sulphur dictated usage of very exotic downhole corrosion resistant alloy (CRA) material. Tightness of carbonate formation (less than 1 mD) pushed to drill 10,000’ horizontal section to meet project objectives. High reservoir pressure reaching 5,700 psi in combination with all conditions above resulted in high level of risk during initial project evaluation and required very robust HSE and Integrity systems in place with no chance to failure.
Arab formation evaluation project started in 2014 and was performed in several steps, with gradual increase of the complexity of the each next stage: from vertical well to horizontal, from sampling to longer duration testing, from carbon steel completion to fit-for-purpose inhibition and high grade CRA materials. Efficient collaboration among multidisciplinary teams, continuous management support and clear communication channels between all stakeholders proved to be a key to success for this challenging project. The project included involvement of high capacity rig to fulfill extended reach depth (ERD) well requirements, specific well intervention techniques while drilling and testing, usage of special inhibitor for high sour wells and finally inspection of the recovered completion. All Company available best practices and technical competencies applied in this project allowed to overcome all the challenges and achieve appreciable sustainable gas rates, meeting all set objectives with no HSE incidents and failures. Findings and lessons learned received are used to tailor next stage of the project to ensure most efficient scenario of field development to support country strategy in increasing energy potential.
The content of the paper gives a good understanding to the readers on the key aspects and main challenges that they may face during initial evaluation stage of the tight gas high pressure high temperature (HPHT) carbonate formations with high H2S content. The document could be used as a local considering current government strategy of massive attraction of new business partners for the exploration of new gas and gas condensate blocks in the region.
Saputelli, Luigi (ADNOC) | Celma, Rafael (ADNOC) | Boyd, Douglas (ADNOC) | Shebl, Hesham (ADNOC) | Gomes, Jorge (ADNOC) | Bahrini, Fahmi (Frontender Corporation) | Escorcia, Alvaro (Frontender Corporation) | Pandey, Yogendra (Prabuddha)
Permeability and rock typing are two of the main outputs generated from the petrophysical domain and are particularly contributors to the highest degree of uncertainty during the history matching process in reservoir modeling, with the subsequent high impact in field development decisions. Detailed core analysis is the preferred main source of information to estimate permeability and to assign rock types; however, since there are generally more un-cored than cored wells, logs are the most frequently applied source of information to predict permeability and rock types in each data point of the reservoir model.
The approach of this investigation is to apply data analytics and machine learning to move from the core domain to the log domain and to determine relationships to then generate properties for the three-dimensional reservoir model with proper simulation for history matching. All wells have a full set of logs (Gamma Ray, Resistivity, Density and Neutron) and few have routine core analysis (Permeability, Porosity and MICP). On a first pass, logs from selected wells are classified into Self Organizing Maps (SOM) without analytical supervision. Then, core data is used to define petrophysical groups (PG), followed by linking the PG's to NMR pore-size distribution analysis results into pre-determined standard pore geometry groups, in this step supervised PGs are generated from the log response constrained by the relationship between pore-throat geometry (MICP) and pose-size distribution (NMR). Permeability-porosity core relationships are reviewed by sorting and eliminating the outliers or inconsistent samples (damaged or chipped, fractures or with local features). After that, the supervised PGs are used to train and calibrate a supervised neural network (NN) and permeability and rock type's relationships can be captured at log scale. Using dimensionality reduction improves the neural network relationships and thus data population into the petrophysical wells.
The result is a more robust model capable to capture over 80% of the core relationships and able to predict permeability and rock types while preserving the geological features of the reservoir. The application of this method makes possible to determine the relevance of core and log data sources to address rock typing and permeability prediction uncertainties. The applied workflows also show how to break the autocorrelation of variables and maximize the usage of logs.
This work demonstrates that the introduced data-driven methods are useful for rock typing determination and address several of the challenges related to core to log properties derivation.