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To say that the shale sector is on the cusp of a new era, one where fast-flowing streams of real-time well data and on-the-fly fracture designs are the norm, is not something one does lightly. It represents a step change that engineers have been told is just around the corner for several years. They've been promised software that will churn out truly optimized recipes of proppant concentration, rate, total volume, etc. to match each fracture stage's piece of the rock. In a neat world, this nets better production from good stages while injecting less capital into bad stages--the ultimate win-win for a sector that spends 60–70% of well costs on the completion. We can pluck example after example from industry literature to prove the incremental existence of such tailor-made well pads.
As the world reaches a tipping point in its will to address climate change, the industry must find a new way forward, especially in the United States. Many are right to say that oil and gas are not going away; the transition is planned to take 30 years or more and will not decline to zero production. This fact, though, obscures the reality that peaking, then declining, demand for oil--gas is another story--will structurally change and globally redistribute the industry's exploration and employment. The story of oil supply and demand began its race to the top 150 years ago. "Shortage" and "glut" have meant that paired growth got out of sync, not that there was a real loss of production.
US shale producers Cabot Oil & Gas and Cimarex Energy are the latest to declare a "merger of equals" in a deal valued at around $17 billion, based on recent equity prices. Announced today, the terms of the deal will result in Cimarex shareholders owning about 50.5% of the combined company and Cabot shareholders owning approximately 49.5%. The deal brings together Houston-based Cabot's gas-rich portfolio, comprising almost 173,000 acres in the Marcellus Shale, with Cimarex's oil-dominated 560,000 net acres in the Permian Basin and Anadarko Basin. On a pro forma basis, the merged company will produce around 600,000 BOE/D from the three basins. The companies expect $100 million in savings to materialize within 2 years of the deal closing and to generate around $4.7 billion in free cash flow from 2022 to 2024.
Degenhardt, John J. (W. D. Von Gonten Laboratories) | Ali, Safdar (W. D. Von Gonten Laboratories) | Ali, Mansoor (W. D. Von Gonten Laboratories) | Chin, Brian (W. D. Von Gonten Laboratories) | Von Gonten, W. D. (W. D. Von Gonten Laboratories) | Peavey, Eric (Shell Fellow-UROC / Texas A&M University)
Abstract Many unconventional reservoirs exhibit a high level of vertical heterogeneity in terms of petrophysical and geo-mechanical properties. These properties often change on the scale of centimeters across rock types or bedding, and thus cannot be accurately measured by low-resolution petrophysical logs. Nonetheless, the distribution of these properties within a flow unit can significantly impact targeting, stimulation and production. In unconventional resource plays such as the Austin Chalk and Eagle Ford shale in south Texas, ash layers are the primary source of vertical heterogeneity throughout the reservoir. The ash layers tend to vary considerably in distribution, thickness and composition, but generally have the potential to significantly impact the economic recovery of hydrocarbons by closure of hydraulic fracture conduits via viscous creep and pinch-off. The identification and characterization of ash layers can be a time-consuming process that leads to wide variations in the interpretations that are made with regard to their presence and potential impact. We seek to use machine learning (ML) techniques to facilitate rapid and more consistent identification of ash layers and other pertinent geologic lithofacies. This paper involves high-resolution laboratory measurements of geophysical properties over whole core and analysis of such data using machine-learning techniques to build novel high-resolution facies models that can be used to make statistically meaningful predictions of facies characteristics in proximally remote wells where core or other physical is not available. Multiple core wells in the Austin Chalk/Eagle Ford shale play in Dimmitt County, Texas, USA were evaluated. Drill core was scanned at high sample rates (1 mm to 1 inch) using specialized equipment to acquire continuous high resolution petrophysical logs and the general modeling workflow involved pre-processing of high frequency sample rate data and classification training using feature selection and hyperparameter estimation. Evaluation of the resulting training classifiers using Receiver Operating Characteristics (ROC) determined that the blind test ROC result for ash layers was lower than those of the better constrained carbonate and high organic mudstone/wackestone data sets. From this it can be concluded that additional consideration must be given to the set of variables that govern the petrophysical and mechanical properties of ash layers prior to developing it as a classifier. Variability among ash layers is controlled by geologic factors that essentially change their compositional makeup, and consequently, their fundamental rock properties. As such, some proportion of them are likely to be misidentified as high clay mudstone/wackestone classifiers. Further refinement of such ash layer compositional variables is expected to improve ROC results for ash layers significantly.
Abstract Logging-while-drilling (LWD) acoustic imaging technology emerged in the past few years as a low-cost solution to detect and characterize fractures in high-angle and horizontal wells. This type of imaging tool works in either water-based or oil-based drilling fluids, making it a competitive choice for logging unconventional shale wells, which are often drilled with oil-based mud. With high-resolution acoustic amplitude and travel-time images, fractures, bedding planes and other drilling-related features can be identified, providing new insights for reservoir characterization and wellbore geomechanics. The quality of LWD acoustic images however is directly affected by drilling parameters and borehole conditions, as the received signal is sensitive to formation property and wellbore changes at the same time. As a result, interpretation can be quite challenging, and caution needs to be taken to differentiate actual formation property changes from drilling-related features or image artifacts. This paper demonstrates the complexity of interpreting LWD acoustic images through multiple case studies. The examples were collected from vertical and horizontal wells in multiple shale plays in North America, with the images logged and processed by different service companies. Depending on the geology and borehole conditions, various features and artifacts were observed from the images, which can be used as a reference for geologists and petrophysicists. Images acquired with different drilling parameters were compared to show the effect of drilling conditions on image quality. Recommendations and best practices of using this new type of image log are also shared.
Swiss oil trader Vitol said on 30 April that its oil and gas subsidiary, Vencer Energy, was buying Hunt Oil Company's assets in the Permian Basin for an undisclosed sum. Media outlets including Bloomberg and Reuters cited sources that pegged the asking price at around $1 billion. Houston-based Vencer was established last year as the trading giant's first foray into the upstream sector. The assets include leases on 44,000 acres in the Midland Basin side of the Permian, with an output about 40,000 BOE/D. "This is an important day for Vencer as it establishes itself as a significant shale producer in the US Lower 48. We expect US oil to be an important part of global energy balances for years to come, and we believe this is an opportune time for investment into an entry platform in the Americas," said Ben Marshall, the head of Vitol's Americas business unit.
Iraq's state-owned Basra Oil Co. (BOC) may end up buying ExxonMobil's operator stake in the giant West Qurna-1 oil field, after Chevron declined the offer and Iraq briefly considered options that included purchases by its Chinese partners. Oil Minister Ihsan Abdul Jabbar told a news conference on 3 May that his ministry is discussing BOC "taking ownership of the Exxon stake in West Qurna-1 and leading the project, as happened with Majnoon," Reuters reported. Like West Qurna-1, Majnoon is in southern Iraq near the Iranian border and is considered one of the world's largest untapped oil reserves. BOC took over the field when Shell and Petronas exited in 2017 citing declining profitability as oil prices fell. As part of a global debt-reduction strategy, ExxonMobil had submitted a request in January to sell its 32.7% stake in the West Qurna-1 field.
John, Blevins (Hibernia Resources) | Van Domelen, Mark (Downhole Chemical Solutions) | West, Zach (Downhole Chemical Solutions) | Rall, Jason (Downhole Chemical Solutions) | Wakefield, Drake (Downhole Chemical Solutions)
Abstract Since the early development of unconventional resource plays, slickwater fracturing fluids have expanded rapidly and are now the most common type of fluid system used in the industry. Slickwater and viscosifying friction reducer (VFR) fluids consist of polyacrylamide (PAM) polymers and are typically delivered to location in a liquid form such as a suspension or emulsion in a hydrocarbon-based carrier fluid. Recently, advances in dry powder delivery operations have provided unique advantages over the liquid versions of FRs including cost savings and improved health, safety and environmental (HSE) aspects. This paper describes the dry powder delivery process and describes the advantages that this new technology has brought to field operations. The method involves delivering polyacrylamide powder for slickwater fracturing treatments directly into the source water on location, thereby eliminating the use of liquid polymer slurries or emulsions. Liquid friction reducers typically contain 20-30% active polymer loading, with the remaining volume being the carrier fluid to keep the polymer in suspension. By delivering 100% powder, several benefits are gained including elimination of truck deliveries of FR liquids to location, reduction of total chemical volumes by 70-80%, reduction of spill hazards, and lower overall chemical costs. Different powders are available for various applications including the use of fresh or produced water, and viscosifying or non-viscosifying polymers. The key technology for "dry on the fly" (DOTF) operations is the powder delivery equipment. Due to the different molecular structures between polyacrylamide and guar polymers, delivering PAM is more technically challenging than guar and requires much higher mixing energy to achieve proper dispersion and hydration. The delivery system described in this paper uses a unique technology which creates the necessary conditions for powder mixing and has been successfully applied on over 350 wells since early 2019, with over 7,000 tons of polymer delivered.
Abstract Well spacing and stimulation design are amongst the highest impact design variables which can dictate the economics of an unconventional development. The objective of this paper is to showcase a numerical simulation workflow, with emphasis on the hydraulic fracture simulation methodology, which optimizes well spacing and completion design simultaneously. The workflow is deployed using Cloud Computing functionality, a step-change over past simulation methods. Workflow showcased in this paper covers the whole cycle of 1) petrophysical and geomechanical modeling, 2) hydraulic fracture simulations and 3) reservoir simulation modeling, followed by 4) design optimization using advanced non-linear methods. The focus of this paper is to discuss the hydraulic fracture simulation methods which are an integral part of this workflow. The workflow is deployed on a dataset from a multi-well pad completed in late 2018 targeting two landing zones in the Vaca Muerta shale play. On calibrated petrophysical and geomechanical model, hydraulic fracture simulations are conducted to map the stimulated rock around the wellbores. Finely gridded base model is utilized to capture the property variation between layers to estimate fracture height. The 3d discrete fracture network (DFN) built for the acreage is utilized to pick the natural fracture characteristics of the layers intersected by the wellbores. The methodology highlights advances over the past modeling approaches by including the variation of discrete fracture network between layers. The hydraulic fracture model in conjunction with reservoir flow simulation is used for history matching the production data. On the history matched model, a design of experiments (DOE) simulation study is conducted to quantify the impact of a wide range of well spacing and stimulation design variables. These simulations are facilitated by the recent deployments of cloud computing. Cloud computing allows parallel running of hundreds of hydraulic fracturing and reservoir simulations, thereby allowing testing of many combinations of stimulation deigns and well spacing and reducing the effective run time from 3 months on a local machine to 1 week on the cloud. Output from the parallel simulations are fitted with a proxy model to finally select the well spacing and stimulation design variables that offer the minimum unit development cost i.e. capital cost-$ per EUR-bbl. The workflow illustrates that stimulation design and well spacing are interlinked to each other and need to be optimized simultaneously to maximize the economics of an unconventional asset. Using the workflow, the team identified development designs which increase EUR of a development area by 50-100% and reduce the unit development cost ($/bbl-EUR) by 10-30%.
Abstract The purpose of this paper is to present a technique to estimate hydraulic fracture (HF) length, fracture conductivity, and fracture efficiency using simple and rapid but rigorous reservoir simulation matching of historical production, and where available, pressure. The methodology is particularly appropriate for analysis of horizontal wells with multiple fractures in tight unconventional or unconventional resource plays. In our discussion, we also analyze the differences between the results from decline curve analysis (DCA) approach and the Science Based Forecasting (SBF) results that this work proposes. When we characterize fracture properties with SBF, we can do a better job of forecasting than if we randomly combine fracture properties and reservoir permeability together in a decline-curve trend. The forecasts are significantly different with SBF, therefore fracture characterization plays an important role and SBF uses this characterization to produce different (and better) forecasts.