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Chevron has confirmed that it and the Gorgon joint venture participants will proceed with the $4-billion Jansz-Io Compression (J-IC) project offshore Western Australia. Nigel Hearne, Chevron Eurasia Pacific exploration and production president, said J-IC represents Chevron's most significant capital investment in Australia since the sanctioning of the Gorgon Stage 2 project in 2018. "Using world-leading subsea compression technology, J-IC is positioned to maintain gas supply from the Jansz-Io field to the three existing LNG trains and domestic gas plant on Barrow Island," Hearne said. "This will maintain an important source of clean-burning natural gas to customers that will enable energy transitions in countries across the Asia Pacific region." A modification of the existing Gorgon development, J-IC will involve the construction and installation of a 27,000-tonne normally unattended floating field control station, approximately 6,500 tonnes of subsea compression infrastructure, and a 135-km submarine power cable linked to Barrow Island.
The Plover Formation is one of two reservoirs in the Ichthys field of the Australian North West Shelf. The objective of this study is to build multiple scenario-based models to optimize development planning in preparation for the upcoming production phase. The authors have integrated data and interpretations of thin sections, cores, well logs, and seismic data to create multiple geological concepts for the field and to identify key geological uncertainties. The Ichthys liquefied natural gas project is one of the world's largest and involves the development of a gas-condensate field in the Browse Basin. The field is approximately 220 km offshore Western Australia and covers an area of approximately 800 km2 with an average water depth of approximately 250 m.
This page provides SPE members access to the July 2021 issue -- digital, pdf, and online. Digital archive of issues back to January 2020 is available – scroll down from the current issue cover. These are the papers synopsized in JPT this month. They are available to SPE members only through 31 August 2021. There are also links to them at the bottom of each related synopsis.
Carnarvon Petroleum has completed the farmout of 50% of the Buffalo project to Advance Energy PLC. On 17 December 2020, Carnarvon announced that Advance Energy would acquire 50% of the Buffalo project off the west coast of Australia by funding the drilling of the Buffalo-10 well up to $20 million on a free carry basis. Advance met this funding requirement and now has a 50% interest in the project. The well is on track to be drilled in late 2021, subject to securing a drilling rig, where the tendering process is already underway. Following the well, the joint venture will acquire development funding from third-party lenders and any additional funding will be provided by Advance as an interest-free loan.
Abstract Faulting is one type of structural trap for hydrocarbon reservoirs. With more and more fields moving toward the brownfield or mature operations stage of life, the opportunity to target bypassed or attic oil in the vicinity of bounding fault(s) is becoming more and more attractive to operators. However, without an effective logging-while-drilling (LWD) tool to locate and map a fault parallel to the well trajectory, it has been challenging and potentially high risk to optimally place a well to drain oil reserves near the fault. Operators often plan these horizontal wells at a significant distance away from the mapped fault position to avoid impacts to the well construction and production of the well. Often, the interpreted fault position, based on seismic data, can have significant lateral uncertainty, and uncertainties attached to standard well survey measurements make it challenging to place the well near the fault. This often results in the wells being placed much farther from the fault than expected, which is not optimal for maximizing recovery. In other cases, due to uncertainty in the location of the fault, the wells would accidentally penetrate the side faults and cause drilling and other issues. Conventional remote boundary detection LWD tools do not assist with locating the fault position, as they only detect formation boundaries above or below the trajectory and not to the side. In this paper, the authors propose a novel approach for mapping features like a fault parallel to the well trajectory, which was previously impossible to map accurately. This new approach utilizes a new class of deep directional resistivity measurements acquired by a reservoir mapping-while-drilling tool. The deep directional resistivity measurements are input to a newly devised inversion algorithm, resulting in high-resolution reservoir mapping on the transverse plane, which is perpendicular to the well path. These new measurements have a strong sensitivity to resistivity in contrast to the sides of the wellbore, making them suitable for side fault detection. The new inversion in the transverse plane is not limited to detecting a side fault; it can also map any feature on the transverse plane to the well path, which further broadens the application of this technology. Using the deep directional resistivity data acquired from a horizontal ultra-ERD well recently drilled in the Wandoo Field offshore Western Australia, the authors tested this approach against the well results and existing control wells. Excellent mapping of the main side fault up to 30 m to the side of the well was achieved with the new approach. Furthermore, the inversion reveals other interesting features like lateral formation thickness variations and the casing of a nearby well. In addition, the methodology of utilizing this new approach for guiding geosteering parallel to side fault in real time is elaborated, and the future applications are discussed.
Abstract Automation is becoming an integral part of our daily lives as technology and techniques rapidly develop. Many automation workflows are now routinely being applied within the geoscience domain. The basic structure of automation and its success of modelling fundamentally hinges on the appropriate choice of parameters and speed of processing. The entire process demands that the data being fed into any machine learning model is essentially of good quality. The technological advances in well logging technology over decades have enabled the collection of vast amounts of data across wells and fields. This poses a major issue in automating petrophysical workflows. It necessitates to ensure that, the data being fed is appropriate and fit for purpose. The selection of features (logging curves) and parameters for machine learning algorithms has therefore become a topic at the forefront of related research. Inappropriate feature selections can lead erroneous results, reduced precision and have proved to be computationally expensive. Experienced Eye (EE) is a novel methodology, derived from Domain Transfer Analysis (DTA), which seeks to identify and elicit the optimum input curves for modelling. During the EE solution process, relationships between the input variables and target variables are developed, based on characteristics and attributes of the inputs instead of statistical averages. The relationships so developed between variables can then be ranked appropriately and selected for modelling process. This paper focuses on three distinct petrophysical data scenarios where inputs are ranked prior to modelling: prediction of continuous permeability from discrete core measurements, porosity from multiple logging measurements and finally the prediction of key geomechanical properties. Each input curve is ranked against a target feature. For each case study, the best ranked features were carried forward to the modelling stage, and the results are validated alongside conventional interpretation methods. Ranked features were also compared between different machine learning algorithms: DTA, Neural Networks and Multiple Linear Regression. Results are compared with the available data for various case studies. The use of the new feature selection has been proven to improve accuracy and precision of prediction results from multiple modelling algorithms.
Abstract Fracture treatments and stage designs for new wells have evolved considerably over the past decade contributingto significant production growth. For example, in the acreage discussed hererecently used higher intensity fracturing methods provided an ~80% increase in recovery rates compared with legacy wells. Older wells completed originally with less efficient techniques can also benefit from these more up-to-date designs and treatments using re-fracturing methods. These offer the prospect of economically boosting production in appropriately selected wells. While adding in-fill wells has often been favored by Operators as a lowerrisk option the number of wells being re-fractured has grown every year for the last decade. In this case study two adjacent Eagle Ford wells, comprising a newly completed and a re-fractured well, allow both methods to be considered and compared. Completion design and fracture treatment effectiveness are evaluated using the uniformity of proppant distribution at cluster and stage level as the primary measure. Perforation erosion measurements from downhole video footage is used as the main diagnostic. Novel data acquisition methods combined with successful well preparation provided comprehensive and high-quality datasets. The subsequent proppant distribution analysis for the two wells provides the highest confidence results presented to date. Clear, repeatable trends in distribution are observed and these are compared across multiple stage designs for both the newly completed and re-fractured well. Variations in design parameters and how these effects distribution and ultimately recovery are discussed. These include changes to perforation count per cluster, cluster spacing, cluster count per stage, stage length, perforation charge size and treatment rates and volumes. As a final consideration production records for the evaluated wells are also discussed. Historical industry data shows that the number of wells being re-fractured increases relative to the number of newly drilled wells being completed during periods of low oil and gas prices. With the industry again facing harsh economic realities an increasing number of decisions will be made on whether new or refractured wells, or a combination of both, provide the best solution to replace otherwise inevitable production decline. This paper attempts to provide a detailed understanding of how proppant distribution, as a significant factor in production for hydraulically fractured wells, can be evaluated and considered in these decisions.
Abstract This paper investigates the technology and business benefits of a web-based model scheduling application, which integrates a transient model to other business applications that provide injection and demand schedules. The application provides a simple method to input complex scenarios, including compressor, regulator, and routing operations. The paper shows how the system allows non-modellers to use a complex transient model, reducing non-optimal operational decisions which could impact the wholesale natural gas price or supply to end user customers such as households or businesses. Other operational metrics are discussed. Introduction and Background Independent System Operators’ (ISOs) and Transmission System Operators’ (TSOs) use of transient pipeline models to manage nominations and allocations is seemingly an easy operational premise. The Australian Energy Market Operator (AEMO) operates the gas Declared Transmission System (DTS) which serves Victoria, a state in Australia. The DTS network consists of approximately 2,200 km of transmission pipelines with various lengths and diameters, and transports gas to a network from up to 10 different suppliers. The high pressure meshed transmission network supplies gas to 148 custody transfer points which spans the geographical extremities of the state. The DTS is becoming increasingly more complex, with changes to flow paths and dynamic demand regimes. AEMO, like other TSOs and ISOs, is utilising transient pipeline models to inform operational strategies. This paper explores the challenges facing ISOs and TSOs in the United Kingdom, The United States, and Victoria Australia. Specific reference is made to AEMO’s gas transmission network. The issues explored cover a range of subjects including financial and macro policy but all lead to the impact on a transmission network. The paper does not attempt to solve each transmission operator’s challenges in detail. However, within the context of AEMO’s operations, it attempts to identify the similarities with other TSOs and highlight how AEMO’s transient hydraulic model helps it deal with its challenges.
The complete paper describes the extensive integrated engineering collaboration and optimization process that allowed an operator to push the drilling and completion envelope to drill a pair of complex, ultra-extended-reach-drilling (ERD) wells in the mature Wandoo field in the Carnarvon Basin offshore Western Australia. The shallow reservoir depth, extreme ERD profile, and high tortuosity requirement for the wells posed significant challenges. These were overcome with extensive planning; integrated engineering designs; application of new technology; good-quality, real-time data interpretation; and strong execution support from both rig site and town. The Wandoo field, in 56 m of water offshore Western Australia, was discovered in 1991 and subsequently developed and placed on production in 1993. The shallow unconsolidated sandstone reservoir consists of a heavily biodegraded oil column overlain by a gas cap and supported by a strong aquifer drive.
Liu, Jingshou (China University of Petroleum, East China) | Ding, Wenlong (Shandong Provincial Key Laboratory of Deep Oil and Gas) | Yang, Haimeng (and Key Laboratory of Deep-Earth Dynamics of Ministry of Natural Resources, Institute of Geology, Chinese Academy of Geological Sciences (Corresponding author) | Liu, Yang (email: firstname.lastname@example.org))
Summary Fractured reservoirs account for more than one-half of the global oil and gas output and thus play a pivotal role in the world’s energy structure. Under diagenesis, rocks become dense, and tectonic fractures easily form under subsequent tectonic movement. These tectonic fractures are the main seepage conduits of tight sandstone reservoirs and are important determinants of whether a tight sandstone reservoir can have high, stable oil and gas production. The influence of multistage tectonic movement has led to well-developed fractures in the Ordos Basin in central China. In the process of reservoir development, the effective stress on the fracture surface increases because of the decrease in pore pressure, and the fracture aperture, porosity, and permeability also change accordingly. Therefore, modeling of the dual porosity and dual permeability of fractured reservoirs requires a dynamic 4D modeling process related to time. In this paper, we propose a 4D modeling method of dual porosity and dual permeability in fractured tight sandstone reservoirs. First, the porosity and permeability distribution of the reservoir matrix are established based on reservoir modeling. Based on geomechanical modeling, the density and occurrence of natural fractures are predicted by the paleostress field. The in-situ stress field is used to analyze the fracture aperture, and the variation in the fracture aperture during the development process is analyzed along with the variation in the in-situ stress in the development process to realize 4D modeling of the porosity and permeability of fractured reservoirs. The total porosity of the fracture is 0 to 8 × 10%, and the principal value of the planar permeability of the fracture is 0 to 3 × 10 µm; the principal value of the fracture permeability is concentrated in the direction of 65 to 70° east-northeast. The simulated fracture porosity stress sensitivity index is distributed between 0 and 0.2, and the fracture permeability stress sensitivity index is distributed between 0 and 0.4. The Young’s modulus of the rock, in-situ stress parameters, and sound velocity in the rock are important factors affecting the fracture stress sensitivity.