Saturation height modelling is a critical input into 3-D based resource volume estimates. Calibrating saturation height models with in-field core data, particularly from the reservoir of interest, helps to reduce the uncertainties in reservoir saturation estimates. Due to paucity of Core data in most fields; Saturation height modelling is usually done with wireline logs only, using analytical equations. These equations sometimes do not have unique solutions with the same set of log data. The accuracy of the derived solutions is further reduced when these fits are derived without calibration to core data. Some of the log-only model-fits may also not have physical meaning even when there are good visual match with saturation profile at well points; thus failing when exported into a reservoir simulator. It is therefore pertinent to find a way of constraining the results from log-derived capillary models with fitting parameters obtained using core data from analogue fields in the absence of in-situ core data in subject field.The paper demonstrates the value in the use of analogue field core data for calibration of log-derived saturation model. ZAN field is a partially appraised field that has been identified for gas development with two well penetration that have complete suite of logs required for reliable saturation estimates and no core data. Log-based Capillary Pressure models were initially built, without any form of core calibration, with very limited success. To improve the quality of the model, capillary pressure measurements from analogue fields were used as building block for an improved capillary pressure model that was subsequently calibrated with logs from the field of interest. This resulted in an improved saturation match at well positions and also improved dynamic model initialisation.
Field development is heavily contingent on the proper delineation of the field's resource volume along with the subsurface uncertainties. For green fields, appraisal drilling reduces uncertainties, but has the potential of cost escalation and delays in project timelines thus making projects less competitive. This study highlights how a fast tracked appraisal/development strategy for 1.7 Tcf of gas development project worth $800mln was developed and approved by the regulatory authorities. The GATOE field under review is in the South East of the Niger delta, Nigeria. The field is 80 km2 in aerial extent. It consists of 11 stacked hydrocarbon-bearing reservoirs of varying thicknesses and, is penetrated by 5 wells. Seven (7) of these reservoirs (3 AG and 4 NAG) with GIIP of 900 Bscf that are ‘ready-to-go’ gas resource were captured in the ‘Tranche-1’ development scope. The remaining 4 reservoirs which are AG reservoirs with uncertainties in the actual oil column were grouped for trench-2 development but will be appraised during the Tranche-1 execution phase. Usually regulatory approval for field development is secured post appraisal drilling. This study however, proposes a concurrent field development and appraisal scheme where development wells (for fairly known reservoirs) are used to also appraise reservoirs with appraisal needs. Thus significantly reducing the number of appraisal wells (from 3 to 1) and ensuring the delivery of fast-tracked field development (early ‘First-gas’ date). The only appraisal well will be drilled at the tranche-1 execution stage. In order to achieve this, a multidisciplinary evaluation of all available data was done in addition to the use of reliable technology. This is with the aim of demonstrating that the fast-tracked gas development will not jeopardise the recovery of any potential oil that may be proved from the appraisal exercise. This study demonstrates the viability of a field development strategy in which ‘freezing’ of a development concept prior to full field appraisal can be achieved. The outcome is a massive reduction in appraisal costs and accelerated field development.
The maturation and development of hydrocarbons in partially appraised fields (PAFs) is often threatened by the high degree of subsurface uncertainty resulting from limited well penetration and paucity of subsurface data in such fields. The uncertainties ranges are sometimes very wide and the resultant cost of further appraisal is so prohibitive that the value and economic indices of carrying out development projects in these fields are severely eroded. For PAFs which are gas-bearing, the challenge is further underscored by the relatively lower price of natural gas and associated higher cost of infrastructure compared to oil. Thus, if not adequately managed, the subsurface uncertainties can go a long way in defining the economic success or failure of planned development projects in PAFs. For this reason, geoscientists and petroleum engineers are tasked with the responsibility of integrating and analysing all available data in the field with the aim of assessing, managing and reducing these uncertainty ranges as much as possible.The OZ field, which is discussed in this paper, is located in the Niger Delta and has a maximum of 6 well penetrations across sixteen (16) reservoirs in a predominantly gas field. Comprehensive data acquisition (electrical surveys and formation pressures and samples) from the last well drilled in the field in 2012, helped eliminate the fluid typing and contact uncertainties in most of the reservoirs.However, for the potentially largest reservoir in the field, the actual fluid contacts (Gas Oil Contact or Hydrocarbon Water Contact) were not logged rather a Gas-Down-To (GDT) and Water-Up-To (WUT) were logged in this reservoir at 100ft apart. With a 100ft column of undifferentiated fluid, the resource volumetric uncertainties varied substantially and if the entire 100 ft column contained hydrocarbon then depending on the type (gas or oil) and ratio, the planned development of the reservoir could easily change from primarily gas to an oil development with a gas-cap blowdown in the future. Hence, the fluid typing and contact delineation emerged as one of the major uncertainties associated with the development of the reservoir and the field at large. To reduce this uncertainty, systematic field reservoir pressure analysis coupled with the integration of other electrical surveys and regional knowledge were applied to significantly minimize the fluid type and contact uncertainties.This paper showcases details of the analysis and its implication in cost reduction and project value enhancement.
The importance of multi-discipline integration in the various phases of hydrocarbon exploitation cannot be over-emphasized. In the past, the various subsurface disciplines, within the oil and gas industry, worked in silo-like organizations which often results in a sub-optimal understanding/evaluation of the subsurface data. However, in recent times, much has been done and written on multi-disciplinary integration and its benefits particularly with respect to subsurface studies. The Zed field, which is the subject of this paper, is a predominantly gas bearing partially appraised field. The field is composed of a series of stacked sandstone reservoirs located in the Niger-Delta Region of Nigeria. Given the limited subsurface data available within the hydrocarbon-bearing areas of the field (only 2 of the 6 wells in the field penetrated the hydrocarbon-bearing sections), one of the biggest challenges of developing this field remain the high level of subsurface uncertainties coupled with the potentially low economic value of further appraisal and development of the field. In order to adequately assess these uncertainties and the economic feasibility of developing the Zed field, a detailed subsurface study involving a full re-evaluation of all potential hydrocarbon bearing sands penetrated by the wells was required. The study, which kicked off with a comprehensive integrated multi-discipline data review and quicklook evaluation, resulted in the identification of two additional reservoirs previously considered too marginal to contain substantial hydrocarbon. This paper details how the systematic, multi-discipline data integration and review of these two reservoirs helped in the identification and determination of higher hydrocarbon volumes in these reservoirs; and how this has helped in improving the economic value of the Zed field development project.
One of the most popular drive mechanisms in hydrocarbon production is water drive. Depending on the subsurface structural orientation, rock and fluid properties anisotropic distribution and the placement of the well amongst others, it could be edge or bottom water drive. These various patterns of water drive mechanisms have varying degrees of impact on the fluid-water contact, hydrocarbon production and ultimately life cycle recoverable volumes. Whether edge or bottom water, the excessive water production mechanism in a typical well are interrelated; insight to which had been provided by Chan, K.S (1995) in his water diagnostic plot. Though the water-oil ratio (WOR) diagnostic plot has been applied widely in zonal isolation, water shut-off, gas shut-off, gel treatment and its modifications into reserves quantification2, 3, 6, there has not been an integrated approach to the excessive water production analysis; guiding our interpretation of the WOR and its time derivative (WOR’) curves with an integrated understanding of the geological, petrophysical and reservoir properties variation. The WOR and WOR’ plots for this study were generated using over 20 years of production data from one of our SPDC fields in the Niger Delta with 11 oil wells and spanning 4 oil reservoirs. The reservoirs were modelled stratigraphically to show different flow zones delineated by different facies. The initial water saturation and permeability contrast were mapped against each flow zone including their relative permeability functions. The interpretation was also spot-checked using reservoir production monitoring (RPM) log result. This paper presents the outcome of an integrated approach to water diagnostic analysis based on the obtained data set with the view to further crystalize the understanding of water production mechanism in the field, proposing fit-for-purpose wells, reservoir & facilities management (WRFM) actions and adding value to global wells and reservoir performance reviews.
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