Africa (Sub-Sahara) Aminex Petroleum Egypt (APE), a subsidiary of UK-based Aminex, discovered oil at its South Malak-2 (SM2) well on the West Esh el Mellaha-2 concession in Egypt. Based on the findings at SM2, a full field development program will be presented to the Egyptian authorities and the joint venture partners before commercial development.
Africa (Sub-Sahara) Eni successfully completed a new production well in the Vandumbu field, 350 km northwest of Luanda and 130 km west of Soyo, in the West Hub of Block 15/06 offshore Angola. The VAN-102 well is being produced through the N'Goma FPSO and achieved initial production of 13,000 BOED. Production from this well and another well in the Mpungi field will bring Block 15/06 output to 170,000 BOED. Anglo African Oil & Gas encountered oil at the TLP-103C well at its Tilapia license offshore the Republic of Congo. The well intersected the targeted Djeno horizon, and wireline logging confirmed the presence of a 12-m oil column in the Djeno. Total started production from the ultra-deepwater Egina field in approximately 1600 m of water 150 km off the coast of Nigeria. At plateau, the field will produce 200,000 B/D.
Bordeori, Krishna (Schlumberger) | Gupta, Vaibhav (Schlumberger) | Sharma, Lovely (Schlumberger) | Narayan, Shashank (Schlumberger) | Talukdar, Dhurba (Oil India Ltd.) | Lama, Tshering (Oil India Ltd.)
Cased hole gravel pack (CHGP) is the most popular method for controlling production of formation sand in oil or gas cased hole wells. CHGP involves the packing of screen and casing annulus, and perforations to inhibit production of formation sand. Success of a CHGP depends on various factors such as perforation packing, cleanliness of completion brine, perforation strategy and minimizing drawdown. Quality of perforation packing aids in minimizing drawdown of gravel pack completions. This led to popularization of high-rate water packs (HRWPs), an evolved sand control method for cased hole wells. HRWPs involve pumping above fracture extension rate and placing gravels outside casing into the critical matrix. This paper discusses maturation process in design, execution, and evaluation methodology devised from a campaign of 16 HRWPs, which included two formation breakdown acid injections, one slim hole completion, two re-stresses and one top-off.
Naharkatiya fields of Oil India Limited, in Assam-Arakan basin are characterized with high degrees of unconsolidated formation sand. Elements of heterogeneity like formation sand ingression rate, PSD, mineralogy and well-profile in these two fields, where most of the HRWP treatments were executed, demanded case-specific pre-gravel-pack workover operations. Installation of screens and pumping of HRWP treatment presented many challenges, such as formation sand ingression, high circulation pressures, uneven slack/pull weights and issues in tool operations. All these challenges were tackled in unique ways and successful HRWP treatments were completed. A holistic approach was developed towards execution of a High Rate Water Pack treatment, by analyzing all interlinked elements such as perforations, cores, cement bond, reservoir saturation, water cut and offset well history. Post-treatment evaluation of HRWPs using bottomhole gauges identified a sequence of downhole events and potential issues during execution phase. Correlating each new HRWP candidate with learnings from previous ones allowed the operator to better plan workover steps towards execution of the sand control treatment. Contingency plans were devised to tackle issues learned from previous wells, and many were successfully tested in the campaign. Production rates and choke strategies were optimized by analysis of offset wells.
This paper presents data analysis of wells while correlating with their offsets. Post-treatment analysis has been discussed and correlations between suspected issues during execution with signatures in bottom-hole gauge data have been presented. Recommendation are further provided for drilling and completion operations. Evolution in design and execution process for case wells has been presented, which can be used as a reference literature for designing case specific sand control treatment program.
Gaurav Seth, Ernesto Valbuena, Soong Tam, Will Da Sie, Hemant Kumar, Brian Arias, and Troy Price, Chevron Summary In this paper we present the results and analyses from an integrated simulation study focused on evaluating and selecting subsea boosting systems. The integrated model uses field-management strategies incorporating flowline routing, field and gathering-network constraints, and rate allocation. Novel techniques to model subsea networks enable selection of the boosting system and provide an improved understanding of dynamic conditions encountered in deepwater assets. The selected boosting system ensures safe and reliable operations while improving the project's net present value. Combining responses from reservoir and network systems into an integrated model to evaluate the subsea design requirements is a unique aspect of this study, because this involves novel modeling techniques for boosting systems (pumps). Analysis of these outputs leads to an improved understanding of field operation strategies, equipment selection and sizing, and production forecasts. The integrated model uses inflow performance relationships (IPRs) from reservoir simulation and vertical lift tables to generate performance curves (PCs), representing well deliverability as a function of tubinghead pressure. Comprehensive field-management logic uses the PCs to determine optimal well operating rates that satisfy all subsurface and surface constraints. This approach reduces a complex set of constraints to a single operating rate. Well operating rate is also a function of the pump power, the pump suction pressure, and the fluid phase behavior across the pumps. The integrated model delivers pump performance within its operating envelope and ensures equipment integrity. Two components of the subsea boosting system, single-and multiphase pumps, drove performance optimization and selection of system operating conditions. The study incorporated a comprehensive analysis of system constraints through implementation of complex field-management rules that accounted for well integrity (completions), performance of network equipment (valves, boosters, pump power requirements), facility capacities, and reservoir deliverability. The integrated study identified the different limiting system constraints throughout the life of the field and improved the overall efficiency of the gathering system. Use of PCs to reduce the constraints to a single operating rate provides tremendous computational performance improvement.
Chemical EOR is an increasingly employed approach used to enhance oil recovery by combining changes in fluids mobility, macroscopic sweep, interfacial tension, etc. to essentially improve, or extend the economic life of a water flood. It includes flooding with polymer, surfactant, alkaline/surfactant, alkaline-surfactant-polymer (ASP), CO2 and / or other miscible gases which is often combined with waterflood (
The paper evaluates the main chemical changes that occur in the system for each EOR approach –– and shows how these changes, including in situ reservoir reactions and the stability/instability of the EOR packages themselves can exacerbate a range of PC-related challenges especially when considering the likely production of up to three different fluids: formation water, the EOR flood medium and any previous flood water from previous secondary recovery
The paper includes modelling results, laboratory results to validate model predictions as well as examples from field case studies to illustrate the impact of the chemical changes referred to above. Specific highlights include the impact of the use of either high- or low-pH EOR fluids on scale control, corrosion control and asphaltenes control; for scale it examines both inhibitor performance
The overall conclusion is that chemical EOR can have significant impact on PC and that these should not just be considered at the design stage and not just for the injection system but also to take into account the impact these may have on production wells following breakthrough of flood waters, showing that essentially each new or exacerbated PC issues can be predicted or at least anticipated with the required degree of confidence before implementation of EOR.
High-resolution discretizations can be advantageous in compositional simulation to reduce excessive numerical diffusion that tends to mask shocks and fingering effects. In this work, we outline a fully implicit, dynamic, multilevel, high-resolution simulator for compositional problems on unstructured polyhedral grids. We rely on four ingredients: (i) sequential splitting of the full problem into a pressure and a transport problem, (ii) ordering of grid cells based on intercell fluxes to localize the nonlinear transport solves, (iii) higher-order discontinuous Galerkin (dG) spatial discretization with order adaptivity for the component transport, and (iv) a dynamic coarsening and refinement procedure. For purely cocurrent flow, and in the absence of capillary forces, the nonlinear transport system can be perturbed to a lower block-triangular form. With counter-current flow caused by gravity or capillary forces, the nonlinear system of discrete transport equations will contain larger blocks of mutually dependent cells on the diagonal. In either case, the transport subproblem can be solved efficiently cell-by-cell or block-by-block because of the natural localization in the dG scheme. In addition, we discuss how adaptive grid and order refinement can effectively improve accuracy. We demonstrate the applicability of the proposed solver through a number of examples, ranging from simple conceptual problems with PEBI grids in two dimensions, to realistic reservoir models in three dimensions. We compare our new solver to the standard upstream-mobility-weighting scheme and to a second-order WENO scheme.
As the oil and gas industry continues to operate in more complex and deeper water environments downhole scale control via scale squeeze treatments becomes an ever-increasing technical challenge. It is therefore essential that effective scale management strategies are adopted which incorporate suitable scale inhibitor (SI) selection, analysis and treatment design procedures to provide optimal and cost-effective squeeze treatment lifetimes to maximise oil production and reduce well intervention costs.
In this paper key factors are evaluated in order to provide a guidance to selecting a suitable treatment strategy for downhole scale control in co-mingled sub-sea well and the impact of chemical retention, minimum inhibitor concentration (MIC), limit of quantifiable detection (LOQD) and well dilution factors on treatment design and strategy are discussed. The pros and cons of different treatment strategies are presented in this paper and consideration is given to following three treatment strategies: Treating all wells with the same chemical and over designing the chemical treatment lifetime ie 18 months and then re-treating all wells after 12 months; Treating individual wells with tagged versions of the same scale inhibitor chemical; Treating individual wells with different scale inhibitors.
Treating all wells with the same chemical and over designing the chemical treatment lifetime ie 18 months and then re-treating all wells after 12 months;
Treating individual wells with tagged versions of the same scale inhibitor chemical;
Treating individual wells with different scale inhibitors.
Options (ii) and (iii) offer the ability to design similar treatment lifetimes for each well but have the flexibility to monitor wells individually and re-squeeze when required.
Examples are provided for treatment options (ii) and (iii) based upon a field example to illustrate the design concepts for fluorescent (F) and phosphorus (P) tagged polymers in two co-mingled wells and a theoretical example for treating three co-mingled wells with different scale inhibitors, one of which could be a phosphonate with two tagged polymers.
This paper presents an overview of the key factors that influence chemical selection and treatment design for co-mingled wells in the same flow line. In addition, it will highlight important concepts to provide guidance for the design of effective treatment strategies for squeezing co-mingled wells in sub-sea and deepwater environments.
Accurate numerical modeling of fluid transport is essential in reservoir management. Higher-order methods help to improve accuracy by reducing the numerical diffusion, which is common for all first order methods. In this paper, we present an implementation of a MUSCL-type second-order finite volume method and demonstrate its capabilities on 2D and 3D unstructured grids. This includes corner point grids that are typically used in reservoir modeling.
A second order finite volume method is compared to standard first order method in terms of accuracy, performance and an ability to handle nonlinearities. There are several ways to build a second order finite volume method. In this paper we choose an optimization-based strategy to compute the steepest possible linear reconstruction. At the same time, a steepness-limiting procedure is included in the optimization as constraint. This ensures that the steepest possible reconstruction that does not lead to oscillations is computed. As a result, sharper fronts compared to standard schemes are obtained.
The paper demonstrates the described method on several benchmark cases with emphasis on relevant for practical reservoir simulation test cases. In particular, we use Norne field open data set, which enables cross validation with other implementations. We test the method on the transport case, where an analytical solution is known, to verify convergence behavior and to isolate the errors. Furthermore, the performance of first- and second-order methods is compared on multiphase flow problems typical for improved oil recovery: solvent and CO2 injection. The second order method shows superior performance in terms of accuracy.
This paper verifies the desirable properties of higher order method for reservoir simulation. Moreover, all the described implementations are available in an open source reservoir simulator Open Porous Media (OPM). As a result, these methods are accessible for reservoir engineers and can be used with industry standard modeling setups.
We present a novel sampling algorithm for characterization and uncertainty quantification of heterogeneous multiple facies reservoirs. The method implements a Bayesian inversion framework to estimate physically plausible porosity distributions. This inversion process incorporates data matching at the well locations and constrains the model space by adding
The proposed workflow uses an ensemble-based Markov Chain Monte Carlo approach combined with sampling probability distributions that are physically meaningful. Moreover, the method targets geostatistical modeling to specific zones in the reservoir. Accordingly, it improves fulfilling the inherent stationarity assumption in geostatistical simulation techniques. Parameter sampling and geostatistical simulations are calculated through an inversion process. In other words, the models fit the known porosity field at the well locations and are structurally consistent within main reservoir compartments, zones, and layers obtained from the seismic impedance volume. The new sampling algorithm ensures that the automated history matching algorithm maintains diversity among ensemble members avoiding underestimation of the uncertainty in the posterior probability distribution.
We evaluate the efficiency of the sampling methodology on a synthetic model of a waterflooding field. The predictive capability of the assimilated ensemble is assessed by using production data and dynamic measurements. Also, the qualities of the results are examined by comparing the geological realism of the assimilated ensemble with the reference probability distribution of the model parameters and computing the predicted dynamic data mismatch. Our numerical examples show that incorporating the seismically constrained models as prior information results in an efficient model update scheme and favorable history matching.
Modelling multiscale-multiphysics geology at field scales is non-trivial due to computational resources and data availability. At such scales it is common to use implicit modelling approaches as they remain a practical method of understanding the first order processes of complex systems. In this work we introduce a numerical framework for the simulation of geomechanical dual-continuum materials. Our framework is written as part of the open source MATLAB Reservoir Simulation Toolbox (MRST). We discretise the flow and mechanics problems using the finite volume method (FVM) and virtual element method (VEM) respectively. The result is a framework that ensures local mass conservation with respect to flow and is robust with respect to gridding. Solution of the coupled linear system can be achieved with either fully coupled or fixed-stress split solution strategies. We demonstrate our framework on an analytical comparison case and on a 3D geological grid case. In the former we observe a good match between analytical and numerical results, for both fully coupled and fixed-stress split strategies. In the latter, the geological model is gridded using a corner point grid that contains degenerate cells as well as hanging nodes. For the geological case, we observe physically plausible and intuitive results given the boundary conditions of the problem. Our initial testing with the framework suggests that the FEM-VEM discretisation has potential for conducting practical geomechanical studies of multiscale systems.