Electrochemically Enhanced Deposition of Scale from Chosen Formation Waters from the Norwegian Continental Shelf

Reservoir formation waters typically contain scaling ions which can precipitate and form mineral deposits. Such mineral deposition can be accelerated electrochemically, whereby the application of potential between two electrodes results in oxygen reduction and water electrolysis. Both processes change the local pH near the electrodes and affect the surface deposition of pH-sensitive minerals. In the context of the plugging and abandonment of wells, electrochemically enhanced deposition could offer a cost-effective alternative to the established methods that rely on setting cement plugs. In this paper, we tested the scale electro-deposition ability of six different formation waters from selected reservoirs along the Norwegian continental shelf using two experimental setups, one containing CO2 and one without CO2. As the electrochemical deposition of scaling minerals relies on local pH changes near the cathode, geochemical modelling was performed to predict oversaturation with respect to the different mineral phases at different pH values. In a CO2-free environment, the formation waters are mainly oversaturated with portlandite at pH > 12. When CO2 was introduced to the system, the formation waters were oversaturated with calcite. The presence of mineral phases was confirmed by powder X-ray diffraction (XRD) analyses of the mineral deposits obtained in the laboratory experiments. The geochemical-modelling results indicate several oversaturated Mg-bearing minerals (e.g., brucite, dolomite, aragonite) in the formation waters but these, according to XRD results, were absent in the deposits, which is likely due to the significant domination of calcium-scaling ions in the solution. The amount of deposit was found to be proportional to the concentration of calcium present in the formation waters. Formation waters with a high concentration of Ca ions and a high conductivity yielded more precipitate.

Remote Cementing Enabled with Automation Drives Reliability, Consistency and Efficiency; A Case History from Norwegian Continental Shelf

Cementing is the fundamental first step and foundation for well construction. The traditional "let's go, mix it, pump it and bump it" cannot be the standard for the current and future offshore cementing operations. As oil and gas operators continue to push the envelope for both innovation and efficiency in well construction operations, to drive energy transition, lower carbon footprint, service providers continue to look for ways to "do more, with less". The latest innovation is redefining offshore cementing operations with a powerful combination of field-proven expertise, equipment, processes, and software. Remote Cementing Operations, the first of its kind in the industry, offers real- time and remote-operation capabilities, controls, and diagnostics of offshore cementing units. While conventional operations would typically involve a cement specialist working in an adjacent room on the rig, Remote Cementing Operations allows all cementing procedures to be controlled offsite by a cementing SME (Subject Matter Expert) from a Remote Operations Center (ROC), miles away from the offshore rig simplifying the operations, minimize errors and improve reliability. As the industry moves forward with a goal to lower carbon footprint, remote cementing enabled by automation will play a key role to implement innovative technologies that will help operators accomplish zonal isolation today and in the future while improving reliability, consistency and driving efficiency. The new implemented process thus results in reduced costs, risks, and non-productive time (NPT) with fewer personnel on-board (POB)—all without sacrificing quality, safety, and performance. A recent success case study is presented, where in an entire offshore well all the cementing operations have been mixed and pumped flawlessly from the ROC in one of the NCS (Norwegian Continental Shelf) rigs. This work explores the relationship between the process of planning, execution and troubleshooting remotely when performing cement operations. By analyzing and reviewing different previous experiences on remote operations, the authors developed a more comprehensive decision support system for remote cementing operations.

The Assumption of Zero Leakage from Permanently Abandoned Wells on the Norwegian Continental Shelf

Quality data is essential for calculations of expected leakage in wells post Permanent Plug and Abandonment (PP&A). Such data may come from surveys studying hydrocarbon leakage to the marine environment. However, recent literature suggests that current regulatory practices for environmental surveys are suboptimal, giving reason to question the assumption that wells have experienced zero leakage from the deep reservoir post PP&A on the Norwegian Continental Shelf (NCS). We investigate whether such an assumption is credible. The credibility of the assumption of zero leakages is investigated through a review of literature addressing the integrity of wells post PP&A on the NCS, with particular emphasis on a 2021 report from the Norwegian Environmental Agency (NEA). Based on the review, the strength of knowledge supporting the assumption that no wells on the NCS have experienced leakages from their deep reservoirs is discussed. The implications of the uncertainty associated with the assumption of zero leakage on the NCS, the rationale for collecting more relevant data, and how these data may be obtained is also discussed in brief. The NEA report details the current regulatory practice for environmental surveys on the NCS. This regulatory practice, as it is described in the NEA report, give limited support to a zero leakage assumption. Norwegian regulations require two environmental surveys post Cessation of Production (CoP). These surveys may however occur in the period between CoP and PP&A, and the closest test stations are generally located 250 meters from the wells. Environmental surveys carried out that far from the well, and possibly prior to PP&A, influence data quality. We argue that the environmental survey data claiming zero leakage, lack sufficient evidence. Thus, based on the reviewed literature outlining the current environmental survey practice, although PP&A well design on the NCS should build on sound principles, we are not able to conclude on the assumption of zero leakage. The interest in risk-based PP&A approaches is increasing globally, and risk-based approaches rely on credible leakage calculations. The failure rates used in these leakage calculations should be based on quality data. The NEA report and other literature indicate that the quality of post PP&A leakage data on the NCS is questionable, and in some cases the data are non-existent. The paper includes suggestions on how to improve the regulatory practice related to environmental surveys.

Quantification and assessment of methane emissions from offshore oil and gas facilities on the Norwegian Continental Shelf

The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian Continental Shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t year−1 (with a mean of 211 t year−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representivity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritizing targeted emission mitigation solutions. Surveys of individual facilities may always require this. However, for field-aggregated emissions, our results show that an accurate estimate of total field-level emissions simply requires a sufficiently large and representative sample of facilities, to yield meaningful comparisons and flux statistics, irrespective of operational status information. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of measurement approaches to validate bottom-up accounting.

De-bubbling Seismic Data using a Generalized Neural Network

Estimating the far-field source signature has always been an important part of seismic processing. However, estimating the source signature from an air gun array is difficult because of the complex interaction between the air bubble oscillations from each air gun, the state of the sea surface, variations in air pressure, the air guns geometry, etc. Removing the bubble noise is important since proper seismic imaging requires a zero-phased, spiky wavelet. De-bubbling has conventionally been done by deconvolution using an (assumed) known source signature. Several methods to estimate the signature and de-bubble the data have been implemented, for instance, source modeling or using near-field hydrophone measurements. We describe an alternative approach using a convolutional neural network for de-bubbling. The network is trained on real data containing a large range of source signatures to make the network robust and adaptive to signature variations. If the signature in the test data is equal to one of the signatures used in the training, the network performs well. Also, if the signature changes in the middle of a sail line, the network can adapt to this change. Moreover, we investigate the network’s sensitivity to changing geology within a survey and on two different surveys on the Norwegian Continental Shelf. If the test data are from similar geology as the training data, the network performs better than if not. Even when applied to a different part of the Norwegian Continental Shelf, the network is still able to remove most of the bubble noise.

Novel Application of Artificial Intelligence with Potential to Transform Well Planning Workflows on the Norwegian Continental Shelf

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.

A Road Map for Renewable Energy Integration with Subsea Processing Systems

This paper proposes a road map for the integration of renewable energy supply to power subsea processing systems. To replace the traditional power supply, like fossil fuel-based generators or grid power, a wind turbine generator (WTG) operating on a islanded mode has been introduced and discussed. A review of the state of the art of WTGs is performed, primarily focused on power and controls aspects, with identification of the main technological gaps left to achieve wind-powered subsea processing. To fully assess the renewable energy integration and current gaps, a study case is proposed which addresses a subsea compression train powered by offshore wind. A thorough analysis is conducted, with meteorological conditions based on the NCS (Norwegian Continental Shelf), where gas line packing is proposed as an innovative means of energy storage. Finally, an economic analysis as well as a CO2 emission estimate is presented to demonstrate the benefits of the proposed road map. Some further discussions and conclusions are presented as well as some propositions for future works.

Identifying Formation Creep: Ultrasonic Bond Logging Field Examples

Summary As part of plug and abandonment (P&A) operations, several acceptance criteria need to be considered by operators to qualify barrier elements. In casing annuli, highly bonded material is occasionally found far above the theoretical top of cement. This paper aims to describe how the highly bonded material can be identified using a combination of ultrasonic logging data, validated with measurements in laboratory experiments using reference cells and how this, in combination with data from the well construction records, can contribute to lowering the costly toll of P&A operations. Ultrasonic and sonic log data were acquired in several wells to assess the bond quality behind multiple casing sizes in an abandonment campaign. Data obtained from pulse-echo and flexural sensors were interactively analyzed with a crossplotting technique to distinguish gas, liquid, barite, cement, and formation in the annular space. Within the methodology used, historical data on each well were considered as an integral part of the analysis. During the original well construction, either water-based mud (WBM) or synthetic oil-based mud (OBM) was used for drilling and cementing operations, and some formation intervals consistently showed high bonding signatures under specific conditions, giving clear evidence of formation creep. Log data from multiple wells confirm that formation behavior is influenced by the type of mud used during well construction. The log data provided information of annulus material with a detailed map of the axial and azimuthal variations of the annulus contents. In some cases, log response showed a clear indication of formation creep, evidenced by a high bond quality around the production casing where cement cannot be present. Based on observations from multiple fields in the Norwegian continental shelf, a crossplot workflow has been designed to distinguish formation from cement as the potential barrier element. NORSOK Standard D-010 (2013) has initial verification acceptance criteria both for annulus cement and creeping formation as a well barrier element, both involving bond logs; however, in the case of creeping formation, it is more stringent stating that “two independent logging measurements/tools shall be applied.” This paper aims to demonstrate how this can be done with confidence using ultrasonic and sonic log data, validated against reference barrier cells (Govil et al. 2020). Logging responses like those gathered during full-scale experiments of reference barrier cells with known defects were observed in multiple wells in the field. Understanding the phenomenon of formation creep and its associated casing bond signature could have a massive impact on P&A operations. With a successful qualification of formation as an annulus barrier, significant cost and time savings can be achieved.