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Journal of Petroleum Technology
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 214066, “Seismic Reprocessing Leads to New Breakthroughs—A Successful Case in the ASH Field, AG Basin in Egypt,” by Mohamed Elokr and Ahmed Lotfy, Kuwait Energy Egypt, and Wei Xing, United Energy Group, et al. The paper has not been peer reviewed. _ The ASH oil field is in the eastern portion of the AG Basin in Egypt. The Lower Cretaceous Alam El Bueib is the main oil-producing formation. Because of the high heterogeneity of the Abu Roash succession, in addition to the influence of thick limestone of the Upper Cretaceous and the influence of multiple complex faults, the quality of seismic data is very poor, requiring seismic reprocessing. Two key techniques were used to achieve the goal: New vertical seismic profile (VSP) well data were acquired to adjust the velocity model, and common reflection angle migration (CRAM) prestack depth migration (PSDM) was used for reprocessing. Introduction The ASH field produces oil from the Aptian Lower Cretaceous reservoir. The ASH structure is interpreted as an elongated east-northeast/west-southwest anticline with intensive breaching on the downthrown side of northwest/southeast to west-northwest/east-southeast-oriented normal faults with obvious signature of synsedimentary activities. The entire area was subject to a series of tectonic events affecting the Western Desert, which led to a complex fault regime clearly recognized in the ASH structure by a series of horizontal displacement across the northwest/southeast faults. Strike/slip to oblique-slip faults also are observed from thicknesses of the cretaceous formations, creating significant difficulty in fault definition. The 3D seismic data acquired in 2007 suffered from losing amplitude of the Lower Cretaceous and deep Jurassic reflectors because of the complex structure. The strong carbonate markers disappear north of the field, where high, dense fault intersection is present closing from the main bounding fault. Loss of seismic amplitude could have severe effects on of the future economics of the field. The seismic survey was reprocessed two times without significant enhancement of the fault imaging. PSDM was run without velocity control, resulting in an uncertain velocity model with inaccurate fault imaging and a mismatching between actual and prognosed depths of the drilled wells of greater than 50 m. This contradiction in reservoir mapping meant that the northern portion of the field remained unexplored. Acquiring VSP in the recently drilled well encouraged reprocessing of the 3D seismic survey using well velocity as a control point in adjusting the seismic velocity model, and application of CRAM technology to improve fault imaging and appraise the uncertain area of the ASH field. CRAM Methodology CRAM was developed as a type of beam migration. Asymptotic ray tracing is performed, assuming that one-way diffraction rays from the subsurface image point to the surface sources and receivers. The takeoff angles from the image point are measured around a given local normal to a background reflection surface for each source ray and receiver ray. A system of source and receiver ray pairs is formed, and the recorded seismic data can be mapped into a local angle domain based on the reflection angles at the subsurface image points.
- Africa > Middle East > Egypt > Western Desert (1.00)
- North America > United States > North Dakota > Bowman County (0.97)
- Africa > Middle East > Egypt > Western Desert > Greater Western Dester Basin > Abu Gharadig Basin > Abu Sennan Concession > ASH Field (0.99)
- Africa > Middle East > Egypt > Western Desert > Bahariya Formation (0.99)
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 22980, “Carbon Storage Leak Detection Through Seismic FWI and RTM: Different Survey Analyses,” by Sajjad Amani, Kyoto University. The paper has not been peer reviewed. Copyright 2023 International Petroleum Technology Conference. Reproduced by permission. _ In the complete paper, marine seismic data processing is investigated as a tool for monitoring possible leakages in geological carbon storage. Because of the great importance of storage permanence, a precise leakage-monitoring strategy is crucial. The proficiency of seismic monitoring solutions for leakage monitoring can be affected by shallower layers as a result of structure, seismic wave attenuation, and leak size. The authors explore two popular seismic monitoring methods used in this application in different scenarios: full waveform inversion (FWI) and reverse-time migration (RTM). Introduction Among the various carbon capture and storage (CCS) options, underground storage in saline aquifers is the best-understood solution. To assure storage consistency and permanence, finding the best strategy to precisely detect possible carbon leaks is essential. A perfect method must demonstrate the difference between stored CO2 and injected CO2 to detect potential fast- and slow-leakage areas. The seismic monitoring technique is the most efficient approach in this respect. Two popular tools for seismic monitoring are FWI and RTM. Several studies of their use in this application have been conducted. However, previous research did not analyze different survey arrays for carbon-leak detection using FWI and RTM. The current research aims to investigate quantitative aspects of CCS monitoring to conduct sensitivity analysis of the three different survey arrays [vertical seismic profile (VSP), crosswell, and surface] for different amounts of CO2-storage leakage in a saline aquifer reservoir. The capability of seismic-imaging methods for small amounts of leakage was tested. Comparison of these three arrays using monitoring methods such as RTM and FWI reveals their pros and cons in providing detailed information about the reservoir. In this research, a simple synthetic model was built that closely fits actual reservoirs characterized by suitable physical features such as velocity and density. Subsequently, elastic wave propagation simulation was implemented by use of a finite-difference scheme over a physical model of the reservoir. Then, FWI was applied to enhance the accuracy of the model parameters. With an efficient forward-modeling and inversion scheme, RTM was used as a powerful imaging tool that provides final high-resolution results for monitoring CO2 migration and possible leakage. This process examined the synthetic model for different amounts of CO2 leakage in saline aquifers to evaluate the performance of CO2 leakage monitoring using the seismic method. The results of the different receiver and source arrays also were compared to establish their effectiveness.
- North America > United States > Illinois > Madison County (0.25)
- Asia > Japan > Kansai > Kyoto Prefecture > Kyoto (0.25)
2023 wrapped up nicely with COP28 in Dubai. The key highlights were the commitments by both governments and the private sector to zero-methane production by 2030, net-zero greenhouse gas emissions from operations by 2050, and triple renewable power-generation capacity and double energy efficiency in this decade. There has been tremendous progress on our collective journey toward cleaner energy production, and now we must take it a notch higher. In the past couple of years, JPT’s Seismic feature has been marked by highly innovative seismic techniques and machine-learning work flows focused on reduction of carbon footprint; frontier exploration, expanding heartlands and brownfield development; and improved seismic survey, imaging, and attribute analysis for reservoir characterization and fracture diagnostics, which are in line with the COP28 pledges. This year’s feature is no different. Recent technical-paper titles have further shown the steady increase in the application of advanced seismic techniques and machine learning to mature “stranded” and “advantaged” hydrocarbon-bearing accumulations to production; improve carbon capture, storage, and leak detection; and analyze naturally and artificially induced fractured reservoirs and seismicity. The selected papers are reflective of these themes. In addition, some remarkable applications of seismic techniques are presented in the recommended papers. They include the following: - 2D nonlinear seismic site response analyses used to determine if the capacity of a silty sedimentation could support the load of a pipeline end termination in the event of an earthquake - The results of a pilot test of the Marine Vibrator, an industry-leading seismic-survey technique - High-resolution modeling to infer if an increase in seismicity is caused by an increase in pore pressure from wastewater injection in the Fort Worth Basin of north central Texas - 4D time/depth shifts and strain signals successfully used to estimate pressure depletion in the Gulf of Mexico Others are applying advanced measurement and modeling techniques to optimally place a long horizontal injector well in multilayered heterogeneous sandstone reservoirs and predicting reservoir presence from seismic velocity and pore-pressure prediction. These topics will supply the insights that will help us achieve the COP28 targets while we look forward to more exciting innovations in 2024. Recommended additional reading at OnePetro: www.onepetro.org. OTC 32267 Seismic Stability Assessment of a Mudmat on Liquefiable Seabed by Brian Carlton, Norwegian Geotechnical Institute, et al. OTC 32393 Predicting Reservoir Presence From Seismic Velocity Mapping and Pore-Pressure Prediction by Matthew James Legg, Shell OTC 32741 Marine Vibrator Milestone: A Pilot Seismic Survey by R. Alfaro, TotalEnergies, et al. SPE 212951 High-Resolution Modeling of Pore-Pressure Change, Fault Slip Potential, and Induced Seismicity in the Fort Worth Basin by Changqing Yao, Texas A&M University, et al. URTeC 3870451 Impact of Fracture Roughness on Fines Migration and Fracture-Aperture Growth in Calcareous Shale Rocks During Acidized Corefloods by Hasan J. Khan, King Fahd University of Petroleum and Minerals, et al.
- North America > United States > Texas > Tarrant County > Fort Worth (0.47)
- Europe > United Kingdom > North Sea > Central North Sea (0.25)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.56)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.56)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.56)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Health, Safety, Environment & Sustainability > Sustainability/Social Responsibility > Sustainable development (1.00)
- Health, Safety, Environment & Sustainability > Environment > Climate change (1.00)
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3864861, “Geomechanics Modeling of Strain-Based Pressure Estimates: Insights From Distributed Fiber-Optic Strain Measurements,” by Wei Ma and Kan Wu, Texas A&M University, and Ge Jin, Colorado School of Mines. The paper has not been peer reviewed. _ The combination of Rayleigh frequency shift distributed strain sensing (RFS-DSS) and pressure-gauge measurements has been reported recently in field applications. The main objective of the study detailed in the complete paper is to investigate the relationship between strain change and pressure change under various fractured reservoir conditions and provide guidelines for better using this novel strain/pressure relationship to estimate conductive fractures and pressure profiles. Introduction With a spatial resolution of 20 cm and a sensitivity of less than 1 με, RFS-DSS can measure mechanical strain changes along the fiber with higher accuracy and sensitivity than low-frequency distributed acoustic sensing measurements. The field applications of RFS-DSS have improved the understanding of near-well and far-field fracture characteristics and the relationship between stimulation and production in unconventional reservoirs. Although some numerical modeling works have been conducted to study the mechanisms of RFS-DSS data sets, the sensitivity, or influencing factors, of the relationship between strain change and pressure change along the fiber are still unclear. In this work, the authors use a coupled geomechanics and fluid-flow simulator to simulate the strain change and pressure change measured along the producing and monitoring wells during both stable production and shut-in periods. Methodology A 3D multilayer reservoir model with dimensions of 300×400×55.82 m was created using Permian Basin data sets. The reservoir was discretized into 553×129×5 gridblocks. To ensure accurate simulation of field RFS-DSS measurements, the mesh was refined around the fracture and wellbore. The fracture width was set to be the same as the RFS-DSS spatial resolution (0.2 m), and the grid size was set to 5 m except for the refined region. As shown in Fig. 1, the reservoir had 11 perforation clusters along the producing well and the monitoring well was 65 m away from the producing well. A fiber cable was installed on both wells to measure the RFS-DSS data set. The producing well was operated for 240 days before being shut in for 4 days, followed by a 1-day reopening and then continued production for 1 year. The pressure decline was 30–40 psi during the 1-day stable production period. Note that the moment after producing 239 days was taken as the reference time to calculate the strain change during the 1-day production (239–240 days) and the moment after 240 days as the reference time to calculate the strain change during the shut-in period (240–244 days).
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (21 more...)
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216856, “ML-Driven Integrated Approach for Perforation Interval Selection Based on Advanced Borehole-Image AI-Assisted Interpretation,” by Alexander Petrov, SPE, Mounir Belouahchia, SPE, and Abdelwahab Noufal, SPE, ADNOC. The paper has not been peer reviewed. _ In the complete paper, the authors propose an artificial-intelligence (AI)-assisted work flow that uses machine-learning (ML) techniques to identify sweet spots in carbonate reservoirs. This process involves annotation of geologic features using a well database, with supervision from subject-matter experts (SMEs). The resulting ML model is tested on new wells and can identify pay zones, perforation intervals, and stress analysis. The models successfully detect fractures, breakouts, bedding planes, vugs, and slippage passages with pixel-level precision, reducing borehole-image (BHI) analysis time. BHI Interpretation and Preprocessing The use of BHIs requires manual interpretation and data identification, heavily relying on the expertise and time of SMEs. A widely adopted approach to address this challenge is the use of supervised computer-vision algorithms, a subfield of AI. These algorithms optimize the task function or model based on examples they have learned from data during training. However, when applied to BHIs, certain ML challenges must be addressed, including the following: - Detecting features in wells from different reservoirs using a model trained on wells from one reservoir can be highly challenging because reservoirs may exhibit distinct geological characteristics. - The handling of parts of BHIs with missing data, depicted by vertically slanted white strips, poses considerable difficulty. Therefore, the authors created a deep-learning approach based on a generative adversarial network architecture to fill the gaps automatically (Fig. 1). - The labels provided by geologists often do not have pixelwise precision, causing the machine to become confused while trying to learn inconsistent patterns. The authors use a convolutional neural network (CNN) to compute a probability map for pixels belonging to specific classes. In this application, a class is defined as any of the heterogeneities in the BHI; however, this method is applicable to any type of heterogeneities in an image. After training, the CNN module provides the optimal probability for each pixel in the image. To classify regions in the BHI based on heterogeneities, a class-specific threshold is established. Pixels with values above the thresholds are assigned to the corresponding class, while those below the thresholds are assigned to the background. BHI-Derived Porosity A new approach for borehole-derived porosity was developed in-house to overcome the limitations of existing techniques widely used in the industry. This approach capitalizes on BHIs for multiple analyses, including structural dip assessment, fault and fracture identification, and determination of minimum and maximum horizontal stress orientation. However, its primary strength lies in quantifying the fraction of secondary porosity in heterogeneous or dual-porosity carbonate formations. The authors have devised a novel method that uses borehole electrical images to conduct porosity and image connectivity analysis. By implementing this technique, essential information can be extracted regarding the spatial distribution of porosity and the extent of secondary porosity fraction.
- Geology > Geological Subdiscipline > Stratigraphy (0.56)
- Geology > Geological Subdiscipline > Geomechanics (0.35)
_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3871303, “Using a Multidisciplinary Approach to Reservoir and Completion Optimization Within the Woodford Shale Play of the Arkoma Basin,” by Stephen C. Zagurski, SPE, and Steve Asbill, SPE, Foundation Energy Management, and Christopher M. Smith, Advanced Hydrocarbon Stratigraphy, et al. The paper has not been peer reviewed. _ Subsurface complexities related to the formation of peripheral foreland basins can have significant effects on unconventional resource development. In the Arkoma Basin of southeast Oklahoma, the onset of thrusting and tectonic loading induced a complex series of dip/slip and strike/slip faults during basin formation. The operator used a series of technologies to increase understanding of the reservoir and its hazards and provide insight into economic implications for future development plans and strategies. Introduction The Woodford is primarily a Type II kerogen source rock. The formation typically is classified as either siliceous mudstone or cherty siltstone. Variable thermal maturity across the basin places the Woodford in both the wet-gas and dry-gas phase windows (moving west to east across the basin). Complex faulting regimes within the Arkoma add a layer of complexity to horizontal development of the Woodford. The operator wanted to increase the understanding of the Woodford and the effects of faulting through the reservoir in a recent development unit in the liquids-rich fairway. The development unit consists of an existing parent well (Well X) and a pair of child wells (Well Y and Well Z). The background of Unit XYZ begins with the completion of parent Well X 4–6 years before infill development. In this portion of the basin, Well X’s initial production rate and its cumulative production to date rank it in the top 25% of wells. The wellbore is subjected to a pair of faults and was drilled in the upper half of the Woodford. Placement of Well X is substantially further east than most parent wells because it is approximately 1,600 ft from the unit boundary. This limited infill development to two wells instead of three; the Arkoma typically has seen spacing of four, and sometimes five, wells per section. Wells Y and Z were planned and drilled east of Well X with 1,100–1,600 ft of well spacing. Well spacing in the unit was slightly hindered by surface location limitations and limited true vertical depth (TVD) between surface casing and landing point. Structural complexity within the unit partially impaired infill development of the unit. Specifically, Well Y and its lateral length was shortened. In this portion of the Arkoma, fault-derived water production typically is the highest-weighted variable in a well’s operating expenditure. Thus, the ability to limit excess water production within Unit XYZ and the surrounding acreage is of paramount importance.
- Geology > Geological Subdiscipline > Geochemistry (1.00)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play (0.91)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.54)
- North America > United States > Oklahoma > Arkoma Basin > Cana Woodford Shale Formation (0.99)
- North America > United States > Oklahoma > Anadarko Basin > Cana Woodford Shale Formation (0.99)
- North America > United States > Arkansas > Arkoma Basin > Cana Woodford Shale Formation (0.99)
The scientific research process begins as one tries to find explanations for a phenomenon. We make observations, define the problem statement, and review the existing domains of research that could be used. Another approach is to explore theoretical problems, those that are purely conceptual at present but provide a solution when a related observation is made in the future. Though these approaches sound isolated, both are part of characterizing uncertainty, and uncertainty comes in all scales and dimensions. This challenges us to learn at all scales possible, from the fume hoods in the laboratory to magnificently exposed outcrops and through deep narrow boreholes that drill through subsurface reservoirs. The combined efforts often convert learnings to actionable intelligence. At a smaller scale, porosity and permeability are probably the two most-studied rock properties among those that have meaningful implications for hydrocarbon reservoirs. Paper SPE 216856 considers machine-learning (ML) methods for classifying reservoir texture at a microscale. Borehole-image logs long have been used to obtain a picture of subsurface reservoirs. Unfortunately, a majority of the observations are qualitative. Quantifying these features faces the challenge of continuity, upscaling, and regional correlation. As we explore the latitude of ML-based applications, the use of these techniques for quantifying image logs becomes very relevant. The authors of that paper contribute to quantifying textural features at a “fume-hood scale” and develop a work flow with the potential for estimating properties such as porosity and permeability from a different domain of reservoir characterization. I often wonder how much the domain on formation evaluation encompasses. While geoscience-driven reservoir characterization is a big part of it, how reservoirs change over time also is a complementary observation. Paper URTeC 3864861 discusses various aspects of geomechanical changes that a hydraulically fractured reservoir goes through during its life cycle. The authors here study the relationship between measured strain from the fiber-optic sensors and wellhead pressure. Research like this could be extended to predicting production profiles and estimating recovery factors, which are important considerations in designing a stimulation program for sustaining production, maximizing recovery, and improving financial matrices for the capital program. I believe information could be categorized as learning, knowledge, and intelligence. Any scientific process starts with set of careful observations bound by an envelope of hypotheses. This is learning. Learning, which could be verified by predictable and repeatable outcomes from carefully designed experiments of complementing domains, becomes knowledge. Actionable knowledge, which then could be used to alter an outcome or a process, becomes intelligence. Paper URTeC 3871303 discusses a development strategy in a restrictive development unit with an existing parent well. Here, considerations are heavily weighted toward optimizing both interwell spacing and capital efficiency. The search for answers to a problem like this must seek guidance from a variable-scale experiment. The study here establishes the big picture with the structural elements of the basin that could restrict both the continuity of the reservoir and the nature of the producible fluid. With this framework, the model is then set to iterate from several different perspectives. Potential interwell communications are explored by measuring fracture-driven interactions (FDIs) and quantifying stimulated reservoir volume. What is impressive here is the different domains from which the authors seek answers. Direct observations from acoustic-fiber measurements for FDI and the geochemistry of produced fluids for identifying unique signatures from vertically separated formations are individual domains that seek the same answers in various scales. The study recommends the optimal spacing between wells and a stimulation design that minimizes well interference, reduces competition for resources between wells, and avoids overcapitalizing the program. This is how knowledge transforms into intelligence. I hope the readers appreciate the scales of characterization in these three papers. As a student of geology, I have always been fascinated by the concept of scale and its relation to the domains of science that we deal with. Unlike general relativity and quantum mechanics, most geologic phenomena are observed in all scales. It is just the uncertainty that needs to be quantified.
_ Subsea production systems have come far in the more than 60 years since the first deployment in the US Gulf of Mexico, helping many countries unlock their offshore hydrocarbon riches in the years that followed. For Brazil, it was a combination of advances in subsea technologies and floating production, storage, and offloading vessel (FPSO) designs that supported the growth of its offshore oil and gas prowess. From those first forays into the Sergipe-Alagoas basin in the northeast during the 1970s, the country’s offshore oil and gas footprint has grown significantly, with today’s production from the pre-salt Campos and Santos basins—located farther from shore and in much deeper water—launching state-run oil company Petrobras to a top spot among the ranks of global producers. The ongoing development of its offshore fields will continue to boost the country’s oil and natural gas production in 2024. Since December 2022, five FPSOs have been brought online, with four installed in 2023 delivering record output. The fifth one—the FPSO Sepetiba—delivered a New Year’s Day surprise when it came online at Mero 2 oil field on 31 December 2023. HISEP, a new subsea technology currently being readied for pilot testing, could potentially ensure continued future production of the Mero field and others by capturing CO2-rich dense gases directly from the wellstream and reinjecting it into the reservoir. The technology also frees up much-needed space and reduces weight on the FPSO’s topside by moving the separation process to the seafloor. Challenges and Solutions Brazil’s challenging offshore pre-salt region—first explored by Petrobras in 2005—contains estimated reserves of 30 to 40 billion BOE and comes with an extensive list of development challenges. Its Santos Basin, for example, lies in ultradeep water with hydrocarbon reservoirs located at extreme depths ranging from 5500 to 7600 m below sea level and under salt layers more than 2000 m thick. But the challenges do not end there. Managing the basin’s high gas/oil ratio (GOR) and CO2 content leaves a significant operational footprint. In OTC 29762, authors from Petrobras noted that developing the pre-salt reservoirs requires “large production facilities with complex gas processing plants that limit the oil processing and storage capacities.” In the paper presented at the 2019 Offshore Technology Conference (OTC) Brasil, the authors said that the gas processing plants for some pre-salt fields with high production indexes, GOR, and CO2 content account for nearly 60% of the total FPSO topsides area. The Santos Basin is home to the Mero oil field, the country’s third-largest pre-salt field and the first under a production-sharing contract awarded to the Petrobras-led Libra Consortium. The field is considered one of the largest hydrocarbon discoveries in the past decade, covering about 320 km of the Libra block and with a net pay zone reaching 420 m filled with 29 °API oil and high productivity, according to Ana Luiza Neder, et al. (OTC 32784).
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > South America Government > Brazil Government (0.91)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Santos Basin > Libra Block > Mero Field (0.99)
- South America > Brazil > Alagoas > South Atlantic Ocean > South Atlantic Ocean > Sergipe-Alagoas Basin (0.99)
- South America > Brazil > Alagoas > Sergipe > South Atlantic Ocean > Sergipe-Alagoas Basin (0.99)
- (2 more...)
Shale gas producer BKV Corp. has made the leap into the US carbon capture and storage (CCS) sector, becoming the latest upstream firm to challenge the idea that only industry giants can make significant moves in this emerging arena. Founded in 2015 as a privately held subsidiary of Thailand’s coal and energy conglomerate Banpu, BKV and its fewer than 400 employees have quickly built the company into the 17 largest gas producer in the US. In addition to its upstream operations in the Barnett and Marcellus shales, BKV’s business model borrows from its Thai energy roots and includes ownership of two natural gas power plants in Texas. But the firm is better known within upstream technical circles for its leadership in refracturing horizontal wells in the Barnett where it is the largest operator both in terms of acreage and flowing wells. No stranger to diversification, BKV is now shifting its focus to CCS—a market anticipated to balloon almost fivefold from $3 billion to over $14 billion by the end of the decade. This growth is being propelled in the US by new legislation offering $85 in tax credits for each ton of CO2 sequestered, effectively turning the greenhouse gas into a valuable commodity. The company’s inaugural CCS project, in collaboration with Dallas-based EnLink Midstream, launched this past November in Bridgeport, Texas. Called the Barnett Zero Project, BKV and its partner are targeting the sequestration of approximately 210,000 mtpa of CO2e. Hitting that target means potentially generating over $17.8 million in annual tax credits, a sum that offers a swift return on investment for those who can manage costs. BKV has also established a new business unit called dCarbon Ventures which is leading a separate CCS joint venture in the Barnett play called Cotton Cove. The $17.6-million project, $9 million of which will be put up by BKV, is expected to begin injecting up to 45,000 mtpa by the end of next year. Beyond that, BKV and its subsidiaries have secured rights for a large-scale project spanning 21,000 acres in neighboring Louisiana which would source its emissions from the industrial and petrochemical plants around the New Orleans area. Steering these ambitious projects is BKV’s CEO, Chris Kalnin, alongside Lauren Read, vice president of the gas company’s dCarbon Ventures. Under their leadership, BKV hopes to achieve net-zero Scope 1 and 2 emissions by next year—decades ahead of most industry reduction targets. The company is not stopping there and is ambitioning to do what most US-based operators have so far refrained from, which is to offset its Scope 3 emissions sometime next decade. In the following Q&A, Kalnin and Read discuss the motivations behind the Barnett Zero Project, its significance in the context of independent producers, and what it signals about BKV’s broader strategy.
- North America > United States > Texas (0.45)
- North America > United States > Louisiana > Orleans Parish > New Orleans (0.24)
- North America > United States > West Virginia > Appalachian Basin > Marcellus Field > Marcellus Shale Formation (0.94)
- North America > United States > Virginia > Appalachian Basin > Marcellus Field > Marcellus Shale Formation (0.94)
- North America > United States > Texas > Fort Worth Basin > Barnett Field > Barnett Shale Formation (0.94)
- (5 more...)
_ The development of efficient technologies for drilling and hydraulically fracturing horizontal wells has enabled the US to more than double hydrocarbon production since 2005 (Fig. 1), thereby providing unprecedented levels of energy security for America. America’s doubling of hydrocarbon output has also held down the price of energy worldwide, and by doing so, accelerated global economic growth. And it has helped reduce the greenhouse gas (GHG) intensity of energy production by backing out “dirtier” forms of energy, such as coal. Energy security—economic growth—reduced GHGs vented to the atmosphere: That’s a winning combination. One that America and many other countries have benefitted from immensely. Given the enormous positive contributions, it is worth noting that 20 years ago, few if any in our industry foresaw the immense potential of this technology, seeing it as being only applicable for extracting gas from ultratight reservoirs like the Barnett Shale, if they were aware of the technology at all. This oversight caused many companies to wait too long before deciding to pursue unconventional reservoirs and caused several of the “shale gas” pioneers to be late in recognizing that hydraulically fractured horizontal wells (HFHWs) could also be successfully applied in liquid-rich plays such as the Eagle Ford and Permian Basin. These are plays that today deliver far more value than that derived from the gas-prone reservoirs that comprised the initial suite of targets. And while events have proven beyond a doubt that HFHWs are a powerful tool for economically extracting hydrocarbons from both gas-prone and liquids-rich unconventional reservoirs, it seems likely that many in our industry are overlooking a third significant application of this technology: The use of HFHWs to extract heat from the Earth’s crust that can be utilized to generate electricity. Old Story, New Horizon What makes this third application particularly compelling as an investment opportunity is that the primary physical challenge that needs to be overcome to achieve attractive rates of return is strikingly similar to that which the oil and gas industry had to surmount to make both gas and liquids-rich unconventional reservoirs economic. The key to success in all of these cases boils down to an ability to create via hydraulic stimulation a sufficiently large amount of conductive, connected, fracture surface area. With this, one can reliably expect per-well production rates to be economic given the extremely slow rate at which hydrocarbons—and heat—move through unconventional reservoirs and the hot, dry, basement rocks that contain the bulk of the world’s geothermal resources. That converting from vertical to horizontal well geometries was critical for unlocking the potential of unconventional hydrocarbon reservoirs is now obvious, with this switch having allowed petroleum engineers to increase per-well fracture surface areas by several orders of magnitude. This move increased per-well flow rates by similar amounts (i.e., from subeconomic flow rates from hydraulically fractured vertical wells (HFVWs) to flow rates of thousands of BOE/D from HFHWs.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.48)
- Energy > Renewable > Geothermal > Geothermal Resource (0.35)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.89)
- North America > United States > Texas > Sabinas - Rio Grande Basin > Eagle Ford Shale Formation (0.89)
- (25 more...)