Summary Samarang field is a 35 year-old oilfield offshore Malaysia that was initially developed by Shell beginning in 1975. The field was relinquished to Petronas Carigali Sdn Bhd (PCSB) in 1995, which continued field operations and were able to significantly reduce the production decline rates. PCSB also transformed the field into a producing hub, allowing development of two small adjacent fields by reducing the required capital costs. However by 2003, the field was in trouble with production declining and reserves dwindling, suggesting field abandonment was on the horizon. Beginning in 2004, PCSB outsourced a major redevelopment evaluation to a multi-disciplinary, international consulting team. They maintained control by using internal expertise to peer review and assist the team's progress throughout the evaluation and at key milestone meetings. This process allowed PCSB to leverage their own organization's skills while using new technology tools employed by the team. The evaluation included a complete review of all static data, literally a seismic to simulation study approach, employing virtually every subsurface discipline in an attempt to unlock the field's remaining value. The results were full-field static and dynamic models covering the entire field and allowing an integrated redevelopment plan. This plan consists of numerous infill producers and selective application of enhanced oil recovery. In addition, several near-field exploratory targets were identified. Field redevelopment is currently being implemented in a phased approach including ongoing production enhancement,sidetracking of idle wells to updip positions,addition of new well jackets for additional development wells, andselective injection into the larger reservoirs with relatively lower primary recovery. The evaluation will provide dividends for years to come with expected doubling of current production and extension of field life for another 15 years. Field Development History and Background Figure 1 shows that the Samarang Field is located offshore Sabah, East Malaysia, about 45 miles (72 km) northwest of the Labuan Gas terminal. The field surrounds a shallow reef with an water depth of 30 feet (9m). Figure 2 summarizes the field's production and development history. Shell was the initial operator and relinquished the concession to PCSB in April 1995. The field was developed in phases with the initial phase including the larger "A" and "B" drilling platforms, separate producing platforms at A, B, and C, and well jackets at C, D, and E. Subsequent development included well jackets at F and G. An additional well jacket "H" was planned by Shell for the east flank development, but was not implemented in 1986 because of low reserves potential and low oil prices. Key dates in the field's development history are as follows:Discovery: 1972 By Sm-1Field Development: 62 Wells (1975-1979) In Smdp-A,B; Smjt-C,D,E with first oil in June 1975Revisit I (86/87): 12 Wells (Smjt-F,G) And 20 S/T on Smdp-A, B and Smjt-C,D,ERevisit II (91/93): 27 Wells S/T, Three Wo and Two New In Smdp-A, B; Smjt-C, D, FPCSB Begins Operating: 1st April 1995Revisit III (97/98): 3 S/T, 1 Hhp Gas and Five New Wells In Smjt-D, F And G.B Revisit (2002): 2 S/T (Sm 52 And Sm 57) and One Recompletion (Sm 42)
The Shushufindi field is located in the Oriente basin of Ecuador. The field was discovered in 1972 and is sparsely developed with about 200 wells covering an area of approximately 400 km2. An initial lithofacies characterization based on capillary pressures, pore throat size distribution, and log derived total porosities and permeabilities has provided a coherent grouping for the reservoir types that matched in over 92% of the wells. The importance of pore throat size in the initial lithofacies characterization has spurred the use of nuclear magnetic resonance (NMR) logs. NMR laboratory measurements on core samples complement the characterization with continuously calibrated pore body size derivations. Furthermore extensive whole core studies have shown that the pore throat size has a substantial impact on the initial oil saturation. Failures to respect this later point had previously generated disappointing oil production results. The challenge for the subsurface and engineering team is to take advantage of a lithofacies-based method to determine appropriate completion intervals and generate reliable production predictions. Open hole wireline log measurements of derived pore bodies size show a good correlation to NMR laboratory measurements on plugs when grouped within the initial lithofacies characterization. These data are used to provide a calibrated continuous pore body size curve based on the NMR binned porosities, and using the inferred initial oil saturation, to estimate the flow capacities for each lithofacies. This approach provides adequate support for selecting the reservoir rock with the best flow capacity, thereby optimizing the well completion. In thin beds where the vertical resolution of standard density and NMR logs is insufficient to discriminate the best facies a modified method has been developed. Very high resolution imaging has been coupled with flushed zone (Rxo) measurements and high frequency dielectric dispersion log to identify the potential production. This paper presents a lithofacies characterization enhancement methodology using NMR derived pore body size as implemented in the Shushufindi field, the results to date, its impact on the selection of completion intervals, and the resulting improvement in production from this technique.
The Shushufindi field is located in the Oriente basin of Ecuador. The field was discovered in 1972 and widely developed with about 247 wells covering an area of approximately 400 km 2 . The implementation of lithofacies characterization in 98% of the existing wells has given a reliable description in about 92% of the wells in the current geomodel, which demonstrates, the validity of the deterministic method.A robust petrophysical rock type (PRT) classification can significantly improve the chances of success for all wells, focusing on layered reservoir rocks recognized as the major energy resource in recent years. The vertical and lateral classification of rock heterogeneity in the form of rock types is critical to understand the flow dynamics of the reservoirs. Well logs are the best option for formation evaluation as they provide high vertical resolution measurements. However, rock type's classification using only well logs interpretation techniques, has its limits.In this paper, we introduce a rock type neural network technique based on Indexed and Probabilistic Self-Organized Mapping (IPSOM) which was designed for the geological interpretation of well log data, facies prediction and optimal derivation of petrophysical parameters. The rock typing was based on cored wells in a 3-step approach. Preliminary rock type identification was based on sedimentology description and routine core analysis. In parallel, it was refined with high pressure mercury injection data to describe accurately the porous media. The porosity and permeability ranges were established to elaborate a sand facies classification represented by Petrophysical Rock Type through Winland method. The neural network was first trained on cored reservoirs, and then propagated to uncored wells using the classification model relationship with electrical logs. Finally using the IPSOM classification model, a permeabilityporosity relationship for each rock type was obtained, providing input to the dynamic model to predict and validate permeability. This paper present a reservoir characterization enhancement technique using neural network, which has proven its utility in refining the dynamic model of the Shushufindi field and directly contributing to the operator by improving production from layered reservoirs.
The "Oriente" basin is located in eastern Ecuador between the Andes Mountains and the Amazon rainforest. In 2012, daily oil production reached 505,000 barrels. The three main oil-bearing Cretaceous formations in the basin are the Hollin, T and U formations. Results from recent extensive coring of the U and Hollin formations showed that the pore size significantly affects oil saturation and production. Therefore, understanding pore size distribution can greatly enhance the success of a well. It is a major challenge to characterize and classify reservoir type and heterogeneity in reservoirs with pore-size variations using only well log data. We used core data from three wells in the U and Hollin formations to validate a new nuclear magnetic resonance (NMR) spectral analysis technique, applied in the echo domain, to estimate the pore-size distribution. In certain carbonate reservoirs in the Middle East, the distribution of pore size classes can be accurately determined by fitting the NMR pulse echoe. The method was blindly tested on three siliciclastic wells from the Oriente basin, and the results were compared with pore-size analysis from mercury-injection and capillary-pressure data. Additionally, a multi-mineral petrophysical model was built for each eall from log measurements, omitting the core data. The porosity derived from the multi-mineral model was used as a porosity input to guide the time-domain inversion of the NMR echo trains. The inversion solves for continuous logs of the porosity, attributed to three pore families, representing the range of pore-body sizes from small to medium to large. After completing the log-based classification into three pore families, the resulting porosity logs were compared to the analysis of core samples for several oilfields. For all formations and in all fields, the core-analysis inversion data was in good agreement with the time-domain NMR inversion results. These results were used to select optimum intervals to be completed and to predict production in the studied fields.
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