When key geological scenario uncertainties, captured in multiple conceptual models, are combined with continuous parameters, the evaluation of a representative sample set quickly becomes unmanageable, laborious and too time consuming to execute. A workflow is presented that enables users to easily model conceptual as well as parametric uncertainties of the reservoir without the necessity of any complex scripting. The chain of models for all concepts is presented in one view, to provide overview of the key differences between concepts used. An ensemble of geologically sound samples can be created taking into account parameter dependencies and probabilities of concepts. The chain of models per concept can easily be (re)executed.
A case study is presented that consists of multiple concepts based on different hierarchical stratigraphic models in combination with different fault models, each of which with its own fluid- (defined contacts per compartment), grid- (sub-layering and areal resolution) and rock property models. Volumetric calculations are run on an ensemble to get static model observables like GRV, Pore Volume, Oil-In-Place, etc., reported by multiple sub-regions of the model in combination with a lease boundary. (When coupled with dynamic simulation, observables like ultimate recovery, break-through timing, etc. could also be obtained). As thousands of realizations were run concurrently, run time was reduced from weeks to hours. Results reveal the distribution and dependency of observables like GRV on top-structure-depth uncertainty and contact-level uncertainty. For in-place volumes the full suite of concepts and other parametric uncertainties including the stochastic uncertainties (i.e. seed) is analyzed. This also enables the identification of the key uncertainties that impact equity the most, which can be of great commercial value during equity negotiations. This workflow demonstrates how, with the power of Cloud computing, rigorous evaluation of multiple concepts combined with many parametric uncertainties has been achieved within practical turn-around times. As such it overcomes the prohibitive hurdles of the past that often have led to simplifications necessary to save time and effort. The result is better decision quality in resource development decisions.
Rizzato, Paolo (Eni S.p.A.) | Castano, Daniele (Eni S.p.A.) | Moghadasi, Leili (Eni S.p.A.) | Renna, Dario (Eni S.p.A.) | Pisicchio, Patrizia (Eni S.p.A.) | Bartosek, Martin (Eni S.p.A.) | Suhardiman, Yohan (Eni Australia Ltd.) | Maxwell, Andrew (Eni Australia Ltd.)
This paper describes the results of an integrated reservoir study aimed at producing hydrocarbons through a sustainable development from a green High Temperature (HT) giant CO2-rich gas field in the Australian offshore. The development concept addressed the complex challenge of exploiting resources while minimizing the carbon impact.
In order to characterize the reservoir in the most detailed way and to describe the fluids behaviour, a 1.8 million active cells compositional model has been built. An analytical aquifer has been coupled in order to represent the boundary conditions of the area.
The faults system, interpreted on seismic data by geophysicists, has been included in the simulation model. The selected development plan includes the re-injection of the produced CO2 into the aquifer of the reservoir itself. The supercritical CO2-brine relative permeability curves at reservoir conditions have been provided by Eni laboratories, where the experiments were performed.
Therefore, a detailed model has been built with the purpose of: Defining producing well and CO2 injector well locations, numbers and phasing to evaluate expected CO2 injectivity and CO2 breakthrough issues; Optimizing the development concept through a risk analysis approach; Estimating the CO2-rich gas injectivity and storage capacity in the saline aquifer of the reservoir; Predicting the behavior of the CO2-rich gas after re-injection (breakthrough timing and plume migration); Maximizing the CO2 sequestration in the reservoir.
Defining producing well and CO2 injector well locations, numbers and phasing to evaluate expected CO2 injectivity and CO2 breakthrough issues;
Optimizing the development concept through a risk analysis approach;
Estimating the CO2-rich gas injectivity and storage capacity in the saline aquifer of the reservoir;
Predicting the behavior of the CO2-rich gas after re-injection (breakthrough timing and plume migration);
Maximizing the CO2 sequestration in the reservoir.
Moreno Ortiz, Jaime Eduardo (Schlumberger) | Klemin, Denis (Schlumberger) | Savelyev, Oleg (Gazprom Neft Middle East B.V.) | Gossuin, Jean (Schlumberger) | Melnikov, Sergey (Gazpromneft STC) | Serebryanskaya, Assel (Gazprom Neft Middle East B.V.) | Liu, Yunlong (Schlumberger) | Gurpinar, Omer (Schlumberger) | Salazar, Melvin (Schlumberger) | Gheneim Herrera, Thaer (Schlumberger)
Use of numerical models to characterize and evaluate reservoir potential is an industry wide practice, with increasingly more development decisions being substantiated by finite difference models. Advances on hardware and software, along with the ability to effectively incorporate accurate process physics, makes simulation a robust tool for field development decisions, particularly on complex operations such as enhanced oil recovery and/or reservoirs with challenging heterogeneity and pore structures. Use of these models does not come without its challenges where data requirements (and use of special characterization both at lab and field level) increase as does the reservoir characterization granularity and thus model sizes. Unsurprisingly the increase of model precision and data requirements amplifies non-uniqueness of the numerical solutions obtained during any field evaluation including field development planning (FDP). Incomplete/inconsistent datasets pose a further challenge to the accuracy (and arguably risk) of the forecasts by introducing further uncertainty on the process characterization. Use of complementary technology such as digital rock, that would enable mitigate impact of such uncertainties in a timely manner -either at field or laboratory level, is thus highly desirable particularly when dealing with enhanced oil recovery. Compounding the non-linearity effect of the EOR agent characterization is the effect of the augmented numerical artifacts (dispersion, dilution, etc) of which complex chemical implementations are prone to, making the upscaling process from laboratory dimensions to field more complex.
Even though coring of rocks is the best way to characterize reservoir and source rocks geologically and petrophysically, this method is considered expensive, having a relatively high cost per foot. Alternatively, side-wall cores and cuttings are widely used in reservoir characterization at a relatively low cost. However, this method has limitations related to cuttings bad physical conditions, size, mixed lithological and mineralogical characteristics which make the commonly used conventional evaluation methods not applicable. This study introduces a robust combination of digital and conventional core analysis methods to overcome these limitations and characterize reservoir and shale cuttings derived from two hydrocarbon-bearing formations in New Zealand.
Initially, all cuttings from both formations were screened based on their cutting sizes and later based on the visually observed textures using the stereomicroscope. This helped in selecting representative cuttings for the main identified textures. These cuttings were CT imaged at a resolution ranging from 40 to 4 microns/voxel resolution in order to confirm their rock textures and sedimentary structures for better characterization results. Next, mercury injection capillary pressure (MICP), X-ray diffraction (XRD), and petrographical analysis were conducted on all selected cuttings with different rock textures in order to understand the pore types, textural variations, diagenetic overprints and mineralogy of the cuttings samples. Then, they were scanned at optimum resolutions using Micro CT and 3D FIB-SEM microscopies. Finally, all acquired images were segmented digitally and 3D rock volumes were created. These volumes were used in computing porosity, permeability, formation factor resistivity (FRF) and poroperm trends digitally using numerical simulation techniques.
Conventional and digital rock analysis showed that the cuttings derived from the reservoir interval are composed of an argillaceous sandstone with a very good computed porosity (18% up to 31%) and permeability (30 to 200 mD). On the other hand, the cuttings derived from the shale source rock interval, which were predominately composed of clay minerals, have a computed porosity of 12% to 13% (mainly inorganic pores) and an absolute permeability in the range of 0.5 to 4 Micro-Darcy. The digital poroperm trend analysis identified distinct poroperm trends for each formation which helped in understanding their petrophysical aspects.
This integration between conventional and digital methods provided better geological and petrophysical understanding of both formations using a limited number of cuttings, less cost and time.
Weijermans, Peter-Jan (Neptune Energy Netherlands B.V.) | Huibregtse, Paul (Tellures Consult) | Arts, Rob (Neptune Energy Netherlands B.V.) | Benedictus, Tjirk (Neptune Energy Netherlands B.V.) | De Jong, Mat (Neptune Energy Netherlands B.V.) | Hazebelt, Wouter (Neptune Energy Netherlands B.V.) | Vernain-Perriot, Veronique (Neptune Energy Netherlands B.V.) | Van der Most, Michiel (Neptune Energy Netherlands B.V.)
The E17a-A gas field, located offshore The Netherlands in the Southern North Sea, started production in 2009 from Upper Carboniferous sandstones, initially from three wells. Since early production history of the field, the p/z plot extrapolation has consistently shown an apparent Gas Initially In Place (GIIP) which was more than 50% higher than the volumetric GIIP mapped. The origin of the pressure support (e.g. aquifer support, much higher GIIP than mapped) and overall behavior of the field were poorly understood.
An integrated modeling study was carried out to better understand the dynamics of this complex field, evaluate infill potential and optimize recovery. An initial history matching attempt with a simulation model based on a legacy static model highlighted the limitations of existing interpretations in terms of in-place volumes and connectivity. The structural interpretation of the field was revisited and a novel facies modeling methodology was developed. 3D training images, constructed from reservoir analogue and outcrop data integrated with deterministic reservoir body mapping, allowed successful application of Multi Point Statistics techniques to generate plausible reservoir body geometry, dimensions and connectivity.
Following a series of static-dynamic iterations, a satisfying history match was achieved which matches observed reservoir pressure data, flowing wellhead pressure data, water influx trends in the wells and RFT pressure profiles of two more recent production wells. The new facies modeling methodology, using outcrop analogue data as deterministic input, and a revised seismic interpretation were key improvements to the static model. Apart from resolving the magnitude of GIIP and aquifer pressure support, the reservoir characterization and simulation study provided valuable insights into the overall dynamics of the field – e.g. crossflows between compartments, water encroachment patterns and vertical communication. Based on the model a promising infill target was identified at an up-dip location in the west of the field which looked favorable in terms of increasing production and optimizing recovery. At the time of writing, the new well has just been drilled. Preliminary logging results of the well will be briefly discussed and compared to pre-drill predictions based on the results of the integrated reservoir characterization and simulation study.
The new facies modeling methodology presented is in principle applicable to a number of Carboniferous gas fields in the Southern North Sea. Application of this method can lead to improved understanding and optimized recovery. In addition, this case study demonstrates how truly integrated reservoir characterization and simulation can lead to a revision of an existing view of a field, improve understanding and unlock hidden potential.
Africa (Sub-Sahara) United Hydrocarbon International finished drilling the Belanga North-1 exploration well located in Doba basin in southern Chad. The well was drilled to a total depth of 1392 m, and encountered three oil-bearing sand intervals--two in the targeted Upper Cretaceous "YO" sands and one in an untested shallower sand. United Hydrocarbon (100%) is the operator. Asia Pacific China National Offshore Oil Corporation discovered natural gas in the Qiongdongan basin, South China Sea. Well Lingshui 17-2--located in the east Lingshui sag portion of the basin at an average water depth of 1450 m--was drilled and completed to a depth of 3510 m. Lingshui 17-2 encountered a gas reservoir with a total thickness of approximately 55 m. Statoil Australia Theta has drilled and completed the Oz-Alpha 1 exploration well in the southern Georgina basin in the Northern Territory, Australia.
JPT Technology Minute Poll: To Which of the Top Five UN Sustainability Development Goals Do You Think the Oil and Gas Industry Will Contribute the Most? The papers identified in the article cover sustainable development of oil and gas resources in various aspects. Flaring and emissions challenges have recently made news headlines around the world. The goal of this article is to engage you with this important topic by presenting a selection of recent SPE papers which address these challenges through various approaches. Operators face a dilemma in balancing the need for mud weight (MW) to remain below the fracture gradient to avoid losses, while also providing sufficient density to block influxes into the well. JPT Technology Minute Poll: Which Technology Would You Choose for Offshore Compression?
Asia Pacific Santos discovered gas with the Corvus-2 well in the Carnarvon Basin, offshore Western Australia. The well, located in permit WA-45-R, in which Santos has a 100% interest, reached a total depth of 3998 m. It intersected a gross interval of 638 m, one of the largest columns discovered across the North West Shelf. Wireline logging to date has confirmed 245 m of net hydrocarbon pay across the target reservoirs. Total SA and partners ExxonMobil and Oil Search have signed a gas agreement with the government of Papua New Guinea that defines the fiscal framework for the Papua LNG project in the country's Eastern Highlands. The plan involves construction of three 2.7-mtpa LNG trains on the existing PNG-LNG plant site at Caution Bay just west of Port Moresby. Total has 31.1% interest, ExxonMobil has 28.3% interest, and Oil Search has 17.7%.
Africa (Sub-Sahara) Eni discovered up to 250 million bbl of light oil in the Ndungu exploration prospect in Block 15/06 offshore Angola. A well in 1076 m of water reached TD of 4050 m and proved a single oil column of approximately 65 m with 45 m of net pay of 35 API oil. Well results indicate production capacity in excess of 10,000 B/D. Eni operates Block 15/06 with 36.8421% Joint venture partners are Sonangol P&P (36.8421%) and SSI Fifteen (26.3158%). Eni discovered gas and condensate on the Akoma prospect in CTP-Block 4 offshore Ghana. The Akoma-1X exploration well was drilled in 350 m of water approximately 50 km offshore and 12 km northwest of the FPSO John Agyekum Kufuor.
The green light for Santos Energy’s drilling program in the McArthur Basin comes after a moratorium on hydraulic fracturing in the Northern Territory was lifted in 2018. After drilling the Dorado-2 appraisal well, operator Santos Energy now expects a big increase in gas resources from predrill estimates, adding to one of the largest oil resources ever found on Australia’s North West Shelf.