The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
- Data Science & Engineering Analytics
The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
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Todorovic, Jelena (SINTEF Industry) | Stroisz, Anna Magdalena (SINTEF Industry) | Duda, Marcin Ireneusz (SINTEF Industry) | Agofack, Nicolaine (SINTEF Industry) | Lange, Torstein (SINTEF Industry) | Nilsen, Nils-Inge (SINTEF Industry) | Aas, Per Gunnar (Disruptive Value Group) | Sefidroodi, Hamidreza (CannSeal, previously/ Interwell, presently) | Ringe, Thomas (CannSeal, previously/ Interwell, presently)
Abstract Development of wellbore sealant alternatives to cements is a topic of high relevance for production and injection wells, permanent plugging and abandonment, and remediation of leakage behind the casing. Some examples of alternative sealants are epoxy-based sealants, geopolymers, and bismuth-based alloys. Depending on the application, sealing materials are expected to encounter challenging downhole conditions, such as corrosive environments (e.g., CO2, H2S) and pressure or thermal cycling. This is especially significant for permanent plugs, where long-term perspective needs to be considered. In this work, we conducted long-term exposure of three polymer-based wellbore sealants (labelled as A, B and C) to an artificial seawater water environment with dissolved H2S gas. The polymer-based sealants are compared to each other and to a Portland G cement blend that was subjected to the same testing procedure. The experiments reported here are a part of a more extensive campaign that aims to study the behaviour of these materials after up to 12 months exposure to H2S. The aging tests were performed as batch-exposure conditions in a pressure cell at 100 °C and 10 bar. Cylindrical (core) samples of the same material were submerged together in artificial seawater in a glass beaker, and a mixture of H2S and nitrogen was dispersed into the seawater. We characterized mechanical properties before and after H2S exposure by unconfined compressive strength (UCS) tests. X-ray micro-computed tomography (CT) was performed to visualize changes potentially induced by the reaction with H2S. After H2S exposure, sealants A and B displayed significant axial and radial deformation during UCS tests (ductile behaviour), which is a very different behaviour compared to a typical wellbore cement. Sealant C exhibited ductile behaviour during compression but without considerable deformation. For comparison, strain at the peak stress was in the order of 200-300 mm/m for sealants A and B, whereas for C it was approximately 60 mm/m, after one month of H2S aging. For all three materials, a decrease of UCS and Young's modulus was observed after H2S exposure. For sealant C, the UCS was still relatively high after three months of aging, at around 70 MPa, which was about 50 % decrease from the reference value. CT results revealed no obvious progression of a reaction front for sealants A, B and C, however, different effects (e.g. change of porosity, precipitation, cracking) were observed throughout the volumes. The unique behaviour of these materials under stress and the possibility of tuning the physical and chemical properties hold vast potential for different applications. One of the long-term goals is to optimize the material properties to make them more suitable for the permanent plugging of both petroleum and CO2 wells.
Abstract Terahertz (THz) spectroscopy is a nondestructive tool used in many industries to analyze materials, including measuring the water content and the distribution of water in biological samples. THz time-domain spectroscopy (THz-TDS) measures the dielectric and structural properties of a sample by probing it with an ultrafast THz pulse and measuring the change in amplitude and phase. In this study, we demonstrate the use of THz-TDS imaging to quickly map lateral (i.e., two-dimensional) variations in microporosity (ϕμ) using the THz attenuation due to water in the pores after clearing the large pores via centrifugation. Three carbonate rock plugs with differing ϕ and pore-size distributions were subsampled for this study. Three water saturation states were produced for each sample: saturated, centrifuged, and dry. At each saturation state, the sample is weighed and imaged using THz-TDS to spatially map and measure ϕμ. The results show that for each sample the ϕμ obtained using THz-TDS imaging is in excellent agreement with that obtained from both mass balance and MICP. In addition, the THz-TDS maps show significant differences in the spatial distribution of the microporosity for samples having similar composition. This method provides a means to measure ϕ and ϕμ while mapping the spatial distribution of ϕμ toward improved petrophysical characterization of carbonate reservoir rocks.
Abstract Combinations of NMR and dielectric measurements frequently address challenging saturation and wettability determinations in conventional reservoirs. When pore structure effects are addressed, the nuclear magnetic resonance (NMR) characteristics are interpreted based on the evaluations of surface relaxivity, and the dielectric structural response is attributed to the “texture” of the rock matrix. Both pore structure descriptors can be improved if the molecular motions and charge mobility common to the measurements are considered. Similar to the dipolar relaxation equivalence of NMR and dielectric correlation time measurements in the Bloembergen, Purcell, and Pound (BPP) model, we develop a relaxation time correlation assuming representative Maxwell-Wagner relaxations. Dielectric dispersion curves for the carbonate matrix and vug pore components demonstrated by Myers are quantified using a dielectric relaxation time (DRT) model. The modeled pore system fractions are spectrally mapped to the NMR T1 or T2 distributions based on enhanced Debye shielding distances correlated with the conductivity. The characterized NMR distributions are validated with micro-CT pore-size determinations and diffusion correlations. The mapped distributions provide petrophysical insight into the frequently used Archie exponent combination (mn) associated with conductivity tortuosity and additional wettability screening criteria.
Olszowska, Daria (The University of Texas at Austin) | Gallardo-Giozza, Gabriel (The University of Texas at Austin) | Crisafulli, Domenico (The University of Texas at Austin) | Torres-Verdín, Carlos (The University of Texas at Austin)
Abstract Due to depositional, diagenetic, and structural processes, reservoir rocks are rarely homogeneous, often exhibiting significant short-range variations in elastic properties. Such spatial variability can have measurable effects on macroscopic mechanical properties for drilling and fluid production operations. We describe a new laboratory method for the acquisition of ultrasonic angle-dependent measurements of reflected waves that delivers high-resolution, continuous descriptions of P- and S-wave velocity along the surface of the rock sample. Reflection coefficient vs. incidence angle is the main source of information about rock elastic properties. The acquired measurements are matched to numerical simulations to estimate P- and S-wave velocity and density of the porous sample and their variations within the rock specimen, hence providing continuous descriptions of sample complexity. Data collected from various locations on the rock specimen are subsequently used to construct two-dimensional (2D) models of elastic properties along the surface of the rock sample. P- and S-wave velocities estimated with this method agree well with acoustic transmission measurements for most homogeneous rocks. The spatial resolution of the method is limited by receiver size, measurement frequency, and incidence angle. At high incidence angles, the surface area sensitive to the measurements increases, and consequently, the spatial resolution of the corresponding reflection coefficient decreases across neighboring rock features.
Zamiri, Mohammad Sadegh (University of New Brunswick) | Guo, Jiangfeng (University of New Brunswick) | Marica, Florea (University of New Brunswick) | Romero-Zerón, Laura (China University of Petroleum (Beijing)) | Balcom, Bruce J. (University of New Brunswick)
Abstract Shale characterization is complicated by low porosity and low permeability. Nano-porosity and a high degree of heterogeneity present further difficulties. H magnetic resonance (MR) methods have great potential to provide quantitative and spatially resolved information on fluids present in porous rocks. The shale MR response, however, is challenging to interpret due to short-lived signals that complicate quantitative signal detection and imaging. Multicomponent signals require high-resolution methods for adequate signal differentiation. MR methods must cope with low measurement sensitivity at low field. In this paper, T1-T2* and Look-Locker T1*-T2* methods were employed to resolve the shale signal for water, oil, and kerogen at high and low field. This permits fluid quantification and kerogen assessment. The T1-T2* measurement was employed to understand and control contrast in the single-point ramped imaging with T1 enhancement (SPRITE) imaging method. This permitted imaging that gave separate images of water and oil. Water absorption/desorption, evaporation, step pyrolysis, and water uptake experiments were monitored using T1-T2* measurement and MR imaging. The results showed (i) the capability of the T1-T2* measurement to differentiate and quantify kerogen, oil, and water in shales, (ii) the characterization of shale heterogeneity on the core plug scale, and (iii) demonstrated the key role of wettability in determining the spatial distribution of water in shales.
Gao, Ying (Shell Global Solutions International) | Sorop, Tibi (Shell Global Solutions International) | Brussee, Niels (Shell Global Solutions International) | van der Linde, Hilbert (Shell Global Solutions International) | Coorn, Ab (Shell Global Solutions International) | Appel, Matthias (Shell International Exploration and Production) | Berg, Steffen (Shell Global Solutions International)
Abstract Trapped gas saturation (Sgr) plays an important role in subsurface engineering, such as carbon capture and storage, H2 storage efficiency as well as the production of natural gas. Unfortunately, Sgr is notoriously difficult to measure in the laboratory or field. The conventional method of measurement—low-rate unsteady-state coreflooding—is often impacted by gas dissolution effects, resulting in large uncertainties of the measured Sgr. Moreover, it is not understood why this effect occurs, even for brines carefully pre-equilibrated with gas. To address this question, we used high-resolution X-ray computed tomography (micro-CT) imaging techniques to directly visualize the pore-scale processes during gas trapping. Consistent with previous studies, we find that for pre-equilibrated brine, the remaining gas saturation continually decreased with more (pre-equilibrated) brine injected and even after the brine injection was stopped, resulting in very low Sgr values (possibly even zero) at the pore-scale level. Furthermore, we were able to clearly observe the initial trapping of gas by the snap-off effect, followed by a further shrinkage of the gas clusters that had no connected pathway to the outside. Our experimental insights suggest that the effect is related to the effective phase behavior of gas inside the porous medium, which due to the geometric confinement, could be different from the phase behavior of bulk fluids. The underlying mechanism is likely linked to ripening dynamics, which involves a coupling between phase equilibrium and dissolution/partitioning of components, diffusive transport, and capillarity in the geometric confinement of the pore space.
Nourani, Meysam (Stratum Reservoir AS) | Pruno, Stefano (Stratum Reservoir AS) | Ghasemi, Mohammad (Stratum Reservoir AS) | Fazlija, Muhamet Meti (Stratum Reservoir AS) | Gonzalez, Byron (Stratum Reservoir AS) | Rodvelt, Hans-Erik (Stratum Reservoir AS)
Abstract In this study, new parameters referred to as rock resistivity modulus (RRM) and true resistivity modulus (TRM) were defined. Analytical models were developed based on RRM, TRM, and Archie’s equation for predicting formation resistivity factor (FRF) and resistivity index (RI) under overburden pressure conditions. The results indicated that overburden FRF is dependent on FRF at initial pressure (ambient FRF), RRM, and net confining pressure difference. RRM decreases with cementation factor and rock compressibility. The proposed FRF model was validated using 374 actual core data of 79 plug samples (31 sandstone and 48 carbonate plug samples) from three sandstone reservoirs and four carbonate reservoirs, measured under four to six different overburden pressures. The developed FRF model fitted the experimental data with an average relative error of 2% and 3% for sandstone and carbonate samples, respectively. Moreover, the applications and limitations of the models have been investigated and discussed. Further theoretical analysis showed that overburden RI is a function of RI at initial pressure, TRM, and net confining pressure difference. The developed models supplement resistivity measurements and can be applied to estimate FRF, RI, and saturation exponent (n) variations with overburden pressure.
Al-Riyami, N. (Exebenus, Stavanger, Norway) | Revheim, O. (Exebenus, Stavanger, Norway) | Robinson, T. S. (Exebenus, Stavanger, Norway) | Batruny, P. (PETRONAS Carigali, Kuala Lumpur, Malaysia) | Meor Hakeem, M. H. (PETRONAS Carigali, Kuala Lumpur, Malaysia) | Tze Ping, G. (Faazmiar Technology Sdn Bhd, Kuala Lumpur, Malaysia)
Abstract O&G operators seek to reduce CAPEX by reducing unit development costs. In drilling operations this is achieved by reducing flat time and bit-on-bottom time. For the last five years, we have leveraged data generated by drilling operations and machine learning advancements in drilling operations. This work is focused on field test results using a real-time global Rate of Penetration (ROP) optimization solution, reducing lost time from sub-optimal ROPs. These tests were conducted on offshore drilling operations in West Africa and Malaysia, where live recommendations provided by the optimization software were implemented by the rig crews in order to test real-world efficacy for improving ROP. The test wells included near-vertical and highly deviated sections, as well as various formations, including claystones, sandstones, limestones and siltstones. The optimization system consisted of a model for estimating ROP, and an optimizer algorithm for generating drilling parameter values that maximize expected ROP, subject to constraints. The ROP estimation model was a deep neural network, using only surface parameters as inputs, and designed to maximize generalizability to new wells. The model was used out-of-the-box, with no specific retraining for the field testing. During field-tests, increased average ROP was observed after following recommendations provided by the optimizer. Compared to offset wells, higher average ROP values were recorded. Furthermore, drilling was completed ahead of plan in both cases. In the Malaysian test well, following the software's advice yielded an increase in ROP from 10.4 to 31 m/h over a 136 m drilling interval. In the West Africa well, total depth was reached ∼24 days ahead of plan, and ∼2.4 days ahead of the expected technical limit. Importantly, the optimization system provided value in operations where auto-driller technologies were used. This work showcases field-test results and lessons learnt from using machine learning to optimize ROP in drilling operations. The final plug-and-play model improves cycle efficiency by eliminating model training before each well and allows instantaneous, real-time intervention. This deployable model is suitable to be utilized anytime, anywhere, with retraining being optional. As a result, minimizing the invisible lost time from sub-optimal ROP and reducing costs associated with on-bottom drilling for any well complexity and in any location is now part of the standard real-time operation solutions. This deployment of technology shows how further optimization of drilling time and reduction in well cost is achievable through utilization of real time data and machine learning.
Abstract Materials development, mechanical design, cutting structure modelling/simulation, advanced manufacturing process are the key necessities for producing high-quality, superior-performing drill bits. Among all, the bit body materials and manufacturing method are the key limiting factors for geometric design and bit life. Conventionally processed materials used for drill bit bodies, either a metal matrix body (Tungsten carbide particles infiltrated with copper alloy binder) or a steel body with hand-applied hardfacing material, have reached the limit of certain properties. Recently, an Additive Manufacturing (AM) method has gained rapid expansion from prototyping to industrial scale production with the capability of building complicated shapes and competitive properties. This paper presents the innovative work that went into developing the AM powder containing extremely hard tungsten carbide particles and directly printing this matrix composite parts then to be used in manufacturing drill bits for challenging drilling applications. Additionally, other benefits of adopting AM technology include minimized greenhouse gas emission (GHGE); thus, boosting sustainability. Multiple field application cases with polycrystalline diamond compact (PDC) drill bits dressed with AM components are presented to show the performance improvement over conventional counterparts.
Zhu, Jun (Vertechs Energy Group) | Zhang, Wei (Vertechs Energy Group) | Zeng, Qijun (Vertechs Energy Group) | Liu, Zhenxing (Vertechs Energy Group) | Liu, Jiayi (PetroChina Southwest Oil & Gas Field Company) | Liu, Junchen (PetroChina Southwest Oil & Gas Field Company) | Zhang, Fengxia (PetroChina Southwest Oil & Gas Field Company) | He, Yu (PetroChina Southwest Oil & Gas Field Company) | Xia, Ruochen (PetroChina Southwest Oil & Gas Field Company)
Abstract In the past decade, the operators and service companies are seeking an integration solution which combines engineering and geology. Since our drilling wells are becoming much more challenging than ever before, it requires the office engineer not only understanding well construction knowledge but also need learn more about geology to help them address the unexpected scenarios may happen to the wells. Then a novel solution should be provided to help engineers understanding their wells better and easier in engineering and geology aspects. The digital twin technology is used to generate a suppositional subsurface world which contains downhole schematic and nearby formation characteristics. This world is described in 3D modelling engineers could read all the information they need after dealt with a unique algorithm engine. In this digital twin subsurface world, the engineering information like well trajectory, casing program, BHA (bottom hole assembly) status, are combined with geology data like formation lithology, layer distribution and coring samples. Both drilling or completion engineers and geologist could get an intuitive awareness of current downhole scenarios and discuss in a more efficient way. The system has been deployed in a major operator in China this year and received lot of valuable feedback from end user. First of all, the system brings solid benefits to operator's supervisors and engineers to help them relate the engineering challenges with according geology information, in this way the judgement and decision are made more reliable and efficiently, also the solution or proposal could be provided more targeted and available. Beyond, the geology information from nearby wells in digital twin modelling could also provide an intuitional navigation or guidance to under-constructed wells avoid any possible tough layers via adjusting drilling parameters. This digital twin system breaks the barrier between well construction engineers and geologists, revealing a fictive downhole world which is based on the knowledge and insight of our industry, providing the engineers necessary information to support their judgement and assumption at very first time when they meet downhole problems. For example, drilling engineers would pay extra attention to control the ROP (rate of penetration) while drilling ahead to fault layer at the first time it is displayed in digital twin system, which prevent potential downhole accident and avoid related NPT (non-production time). The integration of engineering and geology is a must-do task for operators and service companies to improve their performance and reduce downhole risks. Also, it provides an interdisciplinary information to end user for their better awareness and understanding of their downhole asset. Not only help to avoid some possible downhole risks but also benefit on preventing damage reservoir by optimizing the well construction parameters.