Purewal, Satinder (Imperial College) | Juárez Toquero, Fidel (National Hydrocarbons Commission of Mexico) | Simón Burgos, Eduardo (National Hydrocarbons Commission of Mexico) | Meneses-Scherrer, Eduardo J. (National Hydrocarbons Commission of Mexico) | Arellano Sánchez, Elaine A. (National Hydrocarbons Commission of Mexico)
A Pilot project was initiated to classify Oil and Gas projects in 19 Blocks in Mexico using the United Nations Framework Classification (UNFC) which has a unique 3-dimensional evaluation structure with three axes: Economics, Environment and Social viability (E axis), Project Feasibility (F axis) and Geological Knowledge (G axis). The main focus was to capture the environmental and social impact on project classification and resources categorization.
The Pilot project was coordinated by the National Hydrocarbons Commission (CNH) with integrated collaboration from the Energy Ministry (SENER), the Agency for Safety, Energy and Environment (ASEA), and the Petroleum Work Group of UNECE. SPE classification system (i.e. PRMS) has been mapped to UNFC. While PRMS covers oil and gas projects only, UNFC covers all resources e.g. oil and gas, minerals, renewables, nuclear, etc.
The E axis uniquely differentiates UNFC from PRMS by its granular capture of social and environmental issues. A systematic approach was adopted with focus on E and F axes for which a matrix and a decision tree (‘flow chart’) were created for an efficient classification of the hydrocarbon volumes. For the G axis, the volume ranges provided by the project operators were considered to be valid. In the selected 19 blocks, there were 75 projects identified. These were located offshore, onshore and included conventional and unconventional projects with varying degrees of environmental and social issues.
This is the first known exercise using UNFC for integrating social and environmental issues into oil and gas projects for hydrocarbon volumes classification and categorization anywhere globally. The outcome shows the differences between the PRMS and UNFC due to social and environmental conditions. Using UNFC for classification and categorization of all energy sources of a country, a potential tool can be created for making energy policy decisions. This may also assist in meeting Sustainable Development Goals- 2030 adopted by most countries including the UN and The World Bank.
Classification using UNFC assists in identifying the key social and environmental drivers which may be impediments to moving the oil and gas volumes categorizations higher up the value chain. Added granularity in the classifications incorporating environmental and social considerations will assist project financial investment decision making through comparative assessment of objectives and priorities of national, regional and local stakeholders. To the authors’ knowledge, this is a unique Pilot project with significant value-add outcomes which can be replicated in other countries.
Purewal, Satinder (Imperial College) | Pacheco-Roman, Francisco J. (Secretaria de Energia SENER) | Hernández Juárez, Mayelli (Secretaria de Energia SENER) | León Mella, José A. (Agencia de Seguridad Energia y Ambiente) | Mera Avecias, Guillermina (Agencia de Seguridad Energia y Ambiente)
The objective is to present a matrix to identify environmental and social aspects which may impact the initiation, assessment, approval of final investment decision and implementation of oil and gas projects in Mexico. The matrix is applied to 19 blocks. The results demonstrate the usefulness in ease of identification of key elements which may be focus of attention to project feasibility. This may be used as tool for resource classification, and thus adapted to other countries.
The Agency for Safety, Energy and Environment (ASEA) with collaboration from the Energy Ministry (SENER) were involved while the project selection was integrated by the National Hydrocarbon Commission (CNH). CNH selected 19 blocks for review with 75 oil and gas projects. SENER and ASEA developed a matrix with clear identification of environmental and social aspects which may have an impact on the potential implementation of each project. The traffic light and multivariate analysis methods were adopted to colour code the environmental and social elements. This coding allowed quick identification of key areas which need to be addressed for project feasibility.
The selected blocks were located both offshore and onshore with different environmental and social issues. Unconventional and conventional resource developments were covered in the projects. The use of the matrix provided a consistent tool for better identification and understanding of the social and environmental aspects interacting in each block. It also emphasized the main sources of information and the best way to evaluate systematically the social and environmental aspects. The application of the matrix on real blocks exposed the social and environmental aspects that must to be addressed for the oil industry to develop from a sustainable vision. The evaluation of diverse blocks allowed for the identification of common characteristics and the subsequent classification of the blocks. The developed matrix may be used as a tool for making energy policy decisions. At the national level, it may also assist in understanding and meeting some of UN Sustainable Development Goals (SDG's).
This paper presents a novel matrix to identify environmental and social elements relevant for the development of any oil and gas project. It also proposes a useful traffic light and multivariate analysis methods for the evaluation of these elements. The matrix allows quick and easy reference for identification of the key elements which may be focus of attention to oil and gas project feasibility. This approach may benefit the decision-making process within an integrated sustainability perspective.
This paper uses pseudo-time to extend the application of constrained multiwell deconvolution algorithm to gas reservoirs with significant pressure depletion. Multiwell deconvolution is the extension of single well deconvolution to multiple interfering wells. Constraints are added to account for a-priori knowledge on the expected deconvolved derivative behaviors and to eliminate non-physical solutions.
Multiwell deconvolution converts pressure and rate histories from interfering wells into constant-rate pressure responses for each well as if it were producing alone in the reservoir. It also extracts the interference responses observed at each of the other wells due to this single well production. The deconvolved responses have the same duration as the pressure history. This allows to identify reservoir features not visible during individual build ups.
Deconvolution techniques can only be applied to pressure and rate data when flow can be represented by linear equations. In strongly depleted gas reservoirs, fluid properties, and gas compressibility in particular, are pressure dependent, which makes the flow problem non-linear. The paper uses pseudo-pressure and pseudo-time transforms to linearize the problem in such conditions.
The pseudo-time method developed by
The paper extends the application of constrained multiwell deconvolution to strongly depleted gas reservoirs. Constrained multiwell deconvolution is an efficient way to exploit data recorded by permanent downhole pressure gauges and provides information not otherwise available. It can help to identify field heterogeneities and compartmentalization early in field life, making it possible to modify the field development plan and to improve locations of future wells. It can accelerate history-matching with the reservoir model by doing it on the constant rate pressure responses rather than on the actual, usually complex, production history. An added advantage is that comparison between the pressure derivatives of the model and the actual deconvolved derivatives allows identification of mismatch causes.
This paper applies a new constrained multiwell deconvolution algorithm to two field cases: a gas reservoir with two producers, and an oil reservoir with three producers and one injector. Responses given by the constrained multiwell deconvolution are compared with simulations from history-matched reservoir models.
Permanent downhole pressure gauges are routinely installed in most new wells. The resulting large datasets are usually underexploited, however, because it is near impossible to extract information with conventional techniques in the case of well interferences. Multiwell deconvolution (
The published multiwell deconvolution algorithms are extensions of the single-well deconvolution algorithm from von Schroeter
By extracting well and interwell reservoir signatures, multiwell deconvolution allow identification of compartmentalization or unanticipated heterogeneities very early in field life, making it possible to adjust the field development plan and the locations of future wells. In addition, it can accelerate the history-matching process by doing it on constant rate pressure responses rather than on complex production histories. An added advantage is that the comparison between the model derivatives and the actual deconvolved derivatives enables identification of mismatch causes.
In anisotropic rocks such as shale, the value of the maximum principal stress required to cause shear failure depends not only on the other two principal stresses, but also on the angle β between the maximum principal stress and the normal to the bedding plane. According to Jaeger’s plane of weakness model, for β near 0° or 90°, failure will occur at a stress determined by the failure criterion for the “intact rock”, and the failure plane will cut across the bedding planes. At intermediate angles, failure will occur along a bedding plane, at a stress determined by the strength parameters of the bedding plane. Data were analyzed from a set of triaxial (σ2 = σ3) compression tests conducted on a suite of shale samples, at different confining stresses, and a range of angles β and it was found that the data could be fit reasonably well with the four-parameter plane of weakness model. Based on these results, a model has been developed for the stability of boreholes drilled in shales. The fully anisotropic Lekhnitskii-Amadei solution is used to compute the stresses around the borehole wall. The Mogi-Coulomb failure criterion is used for the strength of the “intact rock”, and the plane of weakness model is used for the strength of the bedding planes. The model can be used to predict the minimum mud weight required to avoid shear failure, for arbitrary borehole orientations and anisotropy ratios. The results show the importance of using a fully anisotropic elastic model for the stresses, and using a true-triaxial failure criterion, in borehole stability analysis.
A fundamental problem in rock mechanics is to predict, based on the stress state, whether or not a rock will “fail”. There are several modes of failure, one of the most important being shear failure, in which the initially intact rock breaks along a plane whose orientation is controlled by the orientations and magnitudes of the principal stresses. For isotropic rocks, the simplest and oldest failure criterion is the Coulomb failure criterion (Jaeger et al., 2007), which states that failure will occur if and when
where σ1 ≥ σ2 ≥ σ3 are the three principal stresses, So is the cohesion, Co is the uniaxial compressive strength, β = 45°+(ϕ/2) is the angle between the normal vector to the failure plane and the maximum principal stress, ϕ = tan−1 μ is the angle of internal friction, and μ is the coefficient of internal friction. Many other shear failure criteria have also been proposed (Jaeger et al., 2007; Labuz et al., 2018).
ABSTRACT: Geomechanical discrete fracture networks (DFNs) are grown using a 3D finite element-based fracture mechanics simulator. The influence of the fracture growth rate exponent (β) on the resulting fracture geometry and hydraulic properties of networks is investigated. Previous work has found that β has a complex relationship with the final geometry of geomechanically-grown 2D DFNs. Realistic features evolve during the growth of DFNs as a result of the orientation of the principal stress axis and fracture interaction. High values of β cause interaction effects to be more pronounced, and irregular shaped fractures to be more common. Low values of β are found to produce networks with a balance between selective growth on preferentially oriented and interacting fractures, and significant increases in fracture surface area with computation time. The permeability of DFNs is significantly influenced by anisotropy, which develops in the axes perpendicular to the principal stress direction. For fracture networks with different β values, permeabilities along the principal axes are similar for the same total fracture void space.
ABSTRACT: The growth of fractures within a quasi-brittle rock is computed numerically with the aim of generating high-density geomechanically realistic three-dimensional discrete fracture patterns. Patterns are generated with a finite element-based discrete fracture propagation simulator, in which deformation and flow are numerically computed. These detailed multi-fracture growth simulations study the emergence of patterns as a function of the interaction of fractures and the mechanical effects of pattern evolution on the distribution of apertures in response to in situ stresses.
The growth of multiple interacting fractures is instrumental in understanding how fracture patterns evolve across scales, and how fracture geometry and topology evolves within a group during mixed mode loading. In particular, realistic modeling of hydraulic fracturing is of great interest. However, fracture growth is relevant to a range of other applications, including hydro-geo-mechanical modeling of processes occurring in or near reservoirs, mines, and nuclear waste repositories.
Fracture growth within quasi-brittle rocks involves propagation and interaction across scales. Growth begins from inter-granular and intra-granular micro-fractures, which have been observed to self-organize in a process whereby ‘initially isolated fractures grow and progressively interact, with preferential growth of a subset of fractures developing at the expense of growth of the rest’ (Hooker et al., 2017). Hooker et al. examine over sixty sandstone samples from five different sites, and conclude that the location of fracture clusters is not random but rather controlled by the interaction mechanics of growing fractures. Thus, the authors suggest that initial micro-fracturing in rocks is not random (e.g. Tang et al. 2018) but rather self-organized, leading to scale-dependent mechanisms for selforganization of fractures at larger scales. The formation of dense fractures systems across scales, outside of layer-restricted systems, is briefly investigated in this work.
Modeling the growth of dense fracture networks is challenging, and in general, fracture density is bound to the observation scale, and it must be assumed that a large number of both smaller and larger scale fractures are also present. A range of numerical methods have been applied to model fractures and fracture growth. These including the finite element method (FEM), the extended finite element method (XFEM), the discrete element method (DEM), combinations of FEM and DEM, discontinuous deformation analysis (DDA), the perturbation method, mesh-less, phase-field. These model the growth of multiple fractures both in 2D and 3D, with or without flow. A partial review of these methods can be found in (Lisjak & Grasselli, 2014).
Sk, M. Hassan (Qatar University) | Abdullah, A. M. (Qatar University) | Ko, M. (Quest Integrity Group) | Laycock, N. (Qatar Shell GTL) | Ryan, M. P. (Imperial College) | Williams, D. E. (University of Auckland) | Ingham, B. (Callaghan Innovation Lower Hutt)
The effects of micro-alloying of plain carbon steel with Mo (0.7 wt.%) in the presence of 1 wt.% Cr on the corrosion behaviour and scale protectiveness in CO2 saturated (sweet) brine (0.5 M NaCl) environment, under hydrodynamic conditions, at 80°C in a slightly acidic environment (pH 6.6) were investigated. Potentiostatic current transients suggest that there exists a synergistic interaction of Cr and Mo, which induces more rapid scale crystallization compared to the Mo-free steel. The presence of Mo also suppressed the current passing through corrosion scale. SEM images suggested that 1Cr.0.7Mo steel induced formation of thinner scale with better protectiveness compared to their non-Mo counterparts. From the mechanistic perspective, we suggest that the addition of small amounts of Mo induces formation of a crystalline scale at short times and then it accelerates the growth of that crystalline layer, by modifying the local environment at the steel surface. Modeling of this hypothesis is currently in progress.
The development of high durability and low cost materials able to operate in a broad range of increasingly aggressing exposure conditions is critical for the oil and gas industries. Of the practical exposure conditions in the oil-field and pipelines, acidic pH (constituted of aqueous CO2 and/or H2S) and region specific elevated temperatures are common. In these environments scales are typically formed on the surface of the steel - sulfide or carbonate based; these scales can have varying degrees of protectiveness to the steel surface. The steel can potentially be made more durable therefore, by enhancing the formation of a protective, adherent, non-porous crystalline scale on the surface of the corroding steel. This type of protective scale could in principle be encouraged to form by controlling the most important exposure conditions such as pH and temperature: however as temperature is more or less fixed for a particular location, it is hard to find any practically feasible technique of controlling the exposure temperature. However, if one could control local interfacial pH to be modulated at the surface of the steel, thus enabling precipitation of a protective crystalline scale may be induced. One of the most interesting techniques that can be considered for modifying the local pH is micro-alloying: i.e. incorporating small amount of specific element in a base materials in purpose of achieving the desired properties.
Sour (H2S –containing) environments present a major problem for oil and gas industries: of particular concern is underdeposit corrosion (UDC) which is a type of accelerated localized corrosion observed under deposits (in this case typically iron-sulfides), creating a risk to asset integrity. The mechanism of UDC is not fully understood and there is no consensus on the methods used to evaluate UDC in pipelines. In this work, both planar electrode and 1-dimensional (1D) artificial pit experiments were performed (where the artificial pit acts as an anode in a three-electrode electrochemical cell, simulating an actively dissolving pit). In the 1D case the dissolution kinetics can be measured directly as a function of system variables such as chloride ion concentration, pH values and the existence of different types of deposit at the pit cavity opening. The effects of deposit chemistry and morphology on the electrochemical dissolution behavior are discussed in terms of a transport-controlled model for pit propagation.
With the continued need for fossil fuels, the extraction of oil and gas from significantly sour fields is increasing globally. A major problem in sour (H2S –containing) gas environments is underdeposit corrosion (UDC) which is a type of localized corrosion observed under deposits, in this case typically iron-sulfide scales.1–4 This presents several challenges to system integrity, including an accelerated rate of localized corrosion, and potential catastrophic-premature failure in fluid handling equipment. This creates a risk to asset integrity, leading to financial losses, and significant risk to both humans and the environment.
In oil and gas field brines, in addition to the abundant sand from the formation, there exists several other reactive components mainly carbon dioxide (CO2) and hydrogen sulfide (H2S), which react with the pipeline steel to give iron carbonate (FeCO3) and iron sulfide (FexSy) products respectively, along with oxides. Since H2S is an efficient scale-forming agent, iron sulfide, which is a much less soluble scale than the formed FeCO3, is formed in different phases and stoichiometry.5 These phases are different in properties and can provide different degrees of protection to the bare metal according to the film growth, structure, reactivity and stability.6 The study of the chemical and physical characteristics of the solid deposits and their influence on the bare metal will be helpful for the development of new corrosion inhibitors and mitigation strategies.3,7
Polymer flooding is a proven EOR/IOR process for viscous and light oil reservoirs alike. However, it results in the formation of two shocks front that require simulation models with fine grid blocks to represent field scale fluid movement. Therefore, upscaling is required to transfer such fluid behavior to coarser models. However, most upscaling methods are designed for waterflood only, while upscaling techniques for polymer flood are rarely discussed in the literature.
In this paper, A new upscaling methodology specifically designed for polymer flooding is presented to address such impracticality. The methodology allows the average flow behavior to be captured, including the effects of small scale heterogeneity whilst compensating for the impact of increased numerical diffusion present in coarse grid models.
The method is based on the pore volume weighted method for relative permeability pseudoization first derived by